Предложения со словосочетанием «пессимистический сценарий»
Так что у этого сборника, кроме прогнозов, есть ещё и другая задача – вселить в нас надежду, показав, как наука может смягчить последствия пессимистических сценариев развития событий, включая негативное влияние изменения климата, перенаселённости и пандемий, вызванных устойчивостью микроорганизмов к антибиотикам.
Вполне возможно, что мои оценки и предположения о стремительном росте вероятности глобальных и локальных экологических катастроф на планете излишне пессимистичны, но при оценках экологического риска рассмотрение наиболее пессимистического сценария или наиболее тяжёлого варианта развития опасных событий обязательно и это абсолютно верно.
И только в последние десятилетия стала понятной обществу неотвратимость пессимистического сценария грядущего.
Несмотря на многочисленные пессимистические сценарии постпандемического мира, у нас есть основания для надежд на то, что после пандемии мы проснёмся не в городах-тюрьмах, а в комфортных городах, связанных современными сервисами, пользоваться которыми мы наконец научились, и обнаружим, что стали более внимательными друг к другу и к среде своего обитания.
Квинтэссенцией пессимистического сценария является абсолютное торжество победы зла над добром.
Привет! Меня зовут Лампобот, я компьютерная программа, которая помогает делать
Карту слов. Я отлично
умею считать, но пока плохо понимаю, как устроен ваш мир. Помоги мне разобраться!
Спасибо! Я стал чуточку лучше понимать мир эмоций.
Вопрос: прозвание — это что-то нейтральное, положительное или отрицательное?
Оптимистический и пессимистический сценарии развития банка должны разрабатываться с учётом их возможной реализации в случае отклонения (от базовых) индикаторов развития внешней и внутренней среды деятельности банка и соответствовать требованиям его акционеров.
Такая полярность: с одной стороны, подозрительность и забитость, а с другой стороны, безответственность и отвязность, – побуждает большинство душ к выбору наиболее пессимистического сценария.
Ассоциации к слову «сценарий»
Синонимы к слову «пессимистический»
Синонимы к слову «сценарий»
Сочетаемость слова «сценарий»
- подобный сценарий
новый сценарий
жизненный сценарий - сценарий фильма
сценарий игры
сценарий развития событий - автор сценария
написание сценария
основа сценария - сценарий повторился
сценарий понравился
сценарий назывался - написать сценарий
идти по сценарию
развиваться по сценарию - (полная таблица сочетаемости)
Значение слова «пессимистический»
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ПЕССИМИСТИ́ЧЕСКИЙ, —ая, —ое. Проникнутый пессимизмом; унылый, мрачный. Пессимистический взгляд. (Малый академический словарь, МАС)
Все значения слова ПЕССИМИСТИЧЕСКИЙ
Значение слова «сценарий»
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СЦЕНА́РИЙ, -я, м. 1. Литературно-драматическое произведение (содержащее подробное описание действия и текст речей персонажей), на основе которого создается фильм. (Малый академический словарь, МАС)
Все значения слова СЦЕНАРИЙ
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Дополнительно
Толковый словарь русского языка. Поиск по слову, типу, синониму, антониму и описанию. Словарь ударений.
пессимистичный
ТОЛКОВЫЙ СЛОВАРЬ
ТОЛКОВЫЙ СЛОВАРЬ УШАКОВА
ПЕССИМИСТИ́ЧНЫЙ, пессимистичная, пессимистичное; пессимистичен, пессимистична, пессимистично (книжн.). То же, что пессимистический. Пессимистичный вид. Пессимистичный взгляд на вещи.
ТОЛКОВЫЙ СЛОВАРЬ ОЖЕГОВА
ПЕССИМИСТИ́ЧНЫЙ, -ая, -ое; -чен, -чна. Проникнутый пессимизмом. П. тон.
| сущ. пессимистичность, -и, жен.
ЭНЦИКЛОПЕДИЧЕСКИЙ СЛОВАРЬ
ПЕССИМИСТИ́ЧНЫЙ -ая, -ое; -чен, -чна, -чно. = Пессимисти́ческий. П. взгляд на вещи. П. знакомый. П-ая книга. П. прогноз.
◁ Пессимисти́чность, -и; ж. Пессимисти́чно, нареч.
АКАДЕМИЧЕСКИЙ СЛОВАРЬ
-ая, -ое; -чен, -чна, -чно.
То же, что пессимистический.
Пессимистичный взгляд на вещи.
◊
Индивидуализм, в корне своем, пессимистичен и не может быть иным, ибо не может не переносить сознание оторванности и бессмысленности своего бытия на все процессы жизни. М. Горький, Ответ В. Золотухину.
ОРФОГРАФИЧЕСКИЙ СЛОВАРЬ
пессимисти́чный; кратк. форма -чен, -чна
ФОРМЫ СЛОВ
пессимисти́чный, пессимисти́чная, пессимисти́чное, пессимисти́чные, пессимисти́чного, пессимисти́чной, пессимисти́чных, пессимисти́чному, пессимисти́чным, пессимисти́чную, пессимисти́чною, пессимисти́чными, пессимисти́чном, пессимисти́чен, пессимисти́чна, пессимисти́чно, пессимисти́чны, пессимисти́чнее, попессимисти́чнее, пессимисти́чней, попессимисти́чней
СИНОНИМЫ
прил., кол-во синонимов: 7
прил.
пессимистический
мрачный
безнадежный
предполагающий неблагоприятное развитие событий)
МОРФЕМНО-ОРФОГРАФИЧЕСКИЙ СЛОВАРЬ
ГРАММАТИЧЕСКИЙ СЛОВАРЬ
СЛОВАРЬ ГАЛЛИЦИЗМОВ РУССКОГО ЯЗЫКА
ПЕССИМИСТИЧНЫЙ ая, ое. pessimiste adj. То же, что пессимистический. БАС-1. Типичный интеллектуалист — неизбежно индивидуалист, в корне своем, пессимистичен и не может быть иным, ибо не может не переносить сознание оторванности и бессмысленности своего бытия на все процессы жизни. М. Горький Ответ В. Золотухину. П. вид, П. взгляд на вещи. Уш. 1939. — Лекс. Уш. 1939: пессимисти/чный.
ПОЛЕЗНЫЕ СЕРВИСЫ
Пессимистический сценарий
Cтраница 1
Пессимистический сценарий исходит из худших вариантов работы, оптимистический основан на учете наилучших вариантов исхода, реалистический ( базовый) строится на средних показателях изменения уровня определяющих факторов.
[1]
Но существуют и пессимистические сценарии. Уменьшение населения развитых стран открывает Эльдорадо перед странами большого демографического взрыва. Народы, находящиеся в неблагоприятных условиях, но на подъеме роста населения, могут присвоить себе — добром или силой — земли и ресурсы народов богатых, но находящихся на спаде. Эти последние постепенно будут смешиваться с пришельцами, пока не потеряют свою индивидуальность. Они исчезнут, как исчезли уже многие народы, попав в подобную ситуацию [ Нас было 80 миллиардов.
[2]
Вместе с тем возможен и пессимистический сценарий развития событий.
[3]
Рассмотрим, например, результаты анализа пессимистического сценария. Что касается увеличения капитальных вложений, то эксперты оценят вероятность этого события очень высоко и порекомендуют инвестору отнестись с должным вниманием к такой возможности.
[4]
Анализируя данные табл. 8, можно сделать следующий вывод: пессимистические сценарии не дают отрицательного или близкого к нулю ЧДД; их ЧДД и другие результативные показатели вполне приемлемы для инвестора, если учитывать небольшую вероятность их реализации.
[5]
В основе рекомендаций лежит правило: даже в оптимистическом варианте нельзя оставить проект для дальнейшего рассмотрения, если значение NPV такого проекта отрицательно, и наоборот: пессимистический сценарий в случае получения положительного значения NPV позволяет эксперту судить о приемлемости данного сценария проекта, несмотря на наихудшие прогнозы изменения факторов.
[6]
Автор в полном объеме раскрыл роль риска в хозяйственной деятельности человека, всесторонне охарактеризовал все имеющиеся в арсенале теории вероятностей методы прогнозирования будущего с целью принятия эффективного решения, выбор которого минимизирует возможность пессимистического сценария.
[7]
На рис. 4.13 — рис. 4.15 приведены графики, показывающие три сценария развития предприятия при проведении расчетов предприятия с проектом и без проекта: текущий, пессимистический и оптимистический. В пессимистическом сценарии предполагается, что цены на продукты предприятия будут на 10 % меньше, а затраты на сырье и материалы на 15 % больше. В оптимистическом сценарии предполагается, что цены на продукты предприятия будут на 10 % больше, а затраты на сырье и материалы на 15 % меньше.
[8]
Окно постоянно находится на экране и позволяет, находясь в таблице или графике, выбрать нужный сценарий и просмотреть значения таблицы или графика при значениях варьируемых переменных сценария. Такими сценариями могут быть оптимистический сценарий, пессимистический сценарий и другие. При нажатии в окне на Закончить пакет возвращается к текущему значению.
[9]
Ей показалось, что он может оказаться поворотным для любого пессимистического сценария развития событий.
[10]
Но если ваша цель состоит в том, чтобы исследовать пессимистические сценарии, вам следует сохранить разум незамутненным. Вы не должны отклонять ни одну потенциальную возможность. В частности, вы должны исследовать те рынки, которые центральные банки не контролируют, которые не подвластны административным средствам контроля над рынками, их нельзя даже закрыть.
[11]
Поэтому анализ чувствительности следует производить последовательно ( поэтапно) для наиболее вероятного, реалистического, а также оптимистического и пессимистического сценария.
[13]
В большинстве случаев достаточно разработать три альтернативных сценария: оптимистический, пессимистический и средний. В оптимистическом сценарии описываются события, которые могут произойти при наилучшем стечении обстоятельств, положительной и наиболее благоприятной динамике основных показателей и параметров ситуации. В пессимистическом сценарии высказываются предположения о возможном развитии событий при наименее благоприятных условиях и наихудших параметрах, характеризующих ситуацию в будущем. В среднем сценарии рассматривается прогноз развития событий в неких средних условиях, при которых одни параметры имеют положительную, другие — отрицательную тенденцию изменений. На основе сценариев могут быть подготовлены планы определенных действий, которые следует предпринять в различных условиях. Эти планы являются основой для принятия и реализации решений при развитии событий, предусмотренных по тому или иному сценарию.
[14]
Если, например, для всех сценариев значение NPV положительно, то проект, безусловно, может быть принят. Если значение NPV для всех сценариев отрицательно, то проект должен быть отклонен. При отрицательном значении NPV для пессимистического сценария следует оценить размер возможных потерь и принимать решение с использованием рассмотренных ранее шкал риска.
[15]
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Русский
Морфологические и синтаксические свойства
| падеж | ед. ч. | мн. ч. | |||
|---|---|---|---|---|---|
| муж. р. | ср. р. | жен. р. | |||
| Им. | пессимисти́чный | пессимисти́чное | пессимисти́чная | пессимисти́чные | |
| Р. | пессимисти́чного | пессимисти́чного | пессимисти́чной | пессимисти́чных | |
| Д. | пессимисти́чному | пессимисти́чному | пессимисти́чной | пессимисти́чным | |
| В. | одуш. | пессимисти́чного | пессимисти́чное | пессимисти́чную | пессимисти́чных |
| неод. | пессимисти́чный | пессимисти́чные | |||
| Т. | пессимисти́чным | пессимисти́чным | пессимисти́чной пессимисти́чною | пессимисти́чными | |
| П. | пессимисти́чном | пессимисти́чном | пессимисти́чной | пессимисти́чных | |
| Кратк. форма | пессимисти́чен | пессимисти́чно | пессимисти́чна | пессимисти́чны |
пес—си—ми—сти́ч—ный
Прилагательное, качественное, тип склонения по классификации А. Зализняка — 1*a. Сравнительная степень — пессимисти́чнее, пессимисти́чней.
Корень: -пессим-; суффиксы: -ист-ичн; окончание: -ый [Тихонов, 1996].
Произношение
- МФА: [pʲɪsʲ(ː)ɪmʲɪˈsʲtʲit͡ɕnɨɪ̯]
Семантические свойства
Значение
- то же, что пессимистический ◆ Отсутствует пример употребления (см. рекомендации).
Синонимы
- безнадёжный, обречённый, пессимистический, частич.: мрачный, печальный, унылый
Антонимы
Гиперонимы
Гипонимы
Родственные слова
| Ближайшее родство | |
Этимология
Происходит от ??
Фразеологизмы и устойчивые сочетания
Перевод
| Список переводов | |
Библиография
ПЕССИМИСТИЧЕСКИЙ
- ПЕССИМИСТИЧЕСКИЙ
-
- ПЕССИМИСТИЧЕСКИЙ
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ПЕССИМИСТИ́ЧЕСКИЙ, пессимистическая, пессимистическое (книжн.). прил. к пессимизм и к пессимист; проникнутый пессимизмом. Пессимистическая философия. Пессимистическое настроение. Пессимистически (нареч.) смотреть на что-нибудь.
Толковый словарь Ушакова.
1935-1940.
.
Синонимы:
Смотреть что такое «ПЕССИМИСТИЧЕСКИЙ» в других словарях:
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пессимистический — пессимистичный, мрачный, безнадёжный; грустный, унылый, печальный, обреченный, безнадежный, тоскливый Словарь русских синонимов. пессимистический пессимистичный, мрачный, безнадёжный Словарь синонимов русского языка. Практический справочник. М.:… … Словарь синонимов
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пессимистический — ПЕССИМИЗМ, а, м. Мрачное мироощущение, при к ром человек не верит в будущее, во всём склонен видеть унылое, плохое; противоп. оптимизм. Толковый словарь Ожегова. С.И. Ожегов, Н.Ю. Шведова. 1949 1992 … Толковый словарь Ожегова
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пессимистический — ая, ое. pessimiste adj. Отн. к пессимизму и пессимисту; проникнутый пессимизмом. Пессимистическое воззрение. БАС 1. Эта пессимистическая нотка показалась мне тогда случайной в устах веселого автора веселых рассказов. Короленко А. П. Чехов. Лекс.… … Исторический словарь галлицизмов русского языка
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пессимистический — пессимистичный проникнутый пессимизмом. Новый словарь иностранных слов. by EdwART, , 2009. пессимистический проникнутый пессимизмом. Большой словарь иностранных слов. Издательство «ИДДК», 2007 … Словарь иностранных слов русского языка
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пессимистический — • глубоко пессимистический … Словарь русской идиоматики
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Пессимистический — прил. 1. соотн. с сущ. пессимизм, пессимист, связанный с ними 2. Свойственный пессимизму, характерный для него. 3. Проникнутый пессимизмом. Толковый словарь Ефремовой. Т. Ф. Ефремова. 2000 … Современный толковый словарь русского языка Ефремовой
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пессимистический — пессимистический, пессимистическая, пессимистическое, пессимистические, пессимистического, пессимистической, пессимистического, пессимистических, пессимистическому, пессимистической, пессимистическому, пессимистическим, пессимистический,… … Формы слов
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пессимистический — пессимист ический … Русский орфографический словарь
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пессимистический — … Орфографический словарь русского языка
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пессимистический — ая, ое. Проникнутый пессимизмом; унылый, безрадостный. П. взгляд. П ое настроение. П ие воззрения. П ие предсказания. ◁ Пессимистически, нареч. П. относиться к окружающему … Энциклопедический словарь
Pessimistic Scenarios
John F. Shroder, in Natural Resources in Afghanistan, 2014
Abstract
Pessimistic scenarios for Afghanistan’s future rest particularly on the prospects for ongoing incessant war in the country because of a long list of such things as Pashtun cultural characteristics; neo-environmental determinism with a harsh physical environment leading to environmental and developmental problems; charismatic or “mad” mullahs who encourage bad behaviors; strong ethnic patchworks leading to ethnic cleansing, and the like; repeated foreign invasions; Afghan xenophobia; endemic corruption; land-ownership disputes; Islamicist desire for endless jihad; decades of war, destroyed educational systems, reduced capacity, widespread illiteracy, drug culture, and the purdah culture wherein valuable women are excluded from normal and useful problem solving. In addition are the paranoia, insecurity, and inability of nearby Pakistan to gain the upper hand over the ISI-driven and protected Taliban insurgency enjoying largely unmolested safe haven there, coupled with similar but not as extreme difficulties with fanatically religious Iran as well: the existing environmental basket case of Afghanistan only contributes further fuel to the pessimism. None of these problems is sufficient by itself to keep Afghanistan down, but in aggregate, they seem to have been enough to spoil the country up to now.
Read full chapter
URL:
https://www.sciencedirect.com/science/article/pii/B9780128001356000209
Renewable energy integration as an alternative to the traditional ground-source heat pump system
Cristina Sáez Blázquez, … Diego González-Aguilera, in Energy Services Fundamentals and Financing, 2021
5.5.1.3 CO2 emission factor
The last variable considered in the sensitivity analysis is the CO2 emission factor. Observing Table 5.10, the expected emission factor is 0.399. As in the previous cases, optimistic and pessimistic scenarios have also been analyzed. Thus this factor has been reduced and increased in a 15%, obtaining for the optimistic situation an emission factor of 0.339 and 0.459 for the pessimistic one. Fig. 5.12 shows how the sensitivity to the increase or reduction of the emission factor is approximately the same in both systems. However, as in the previous cases, the sensitivity of the conventional system is higher compared to the suggested one.
Figure 5.12. Sensitivity analysis to the variation of the CO2 emission factor. Op, optimistic scenario; Ex, expected scenario; Pe, pessimistic scenario.
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Pathophysiology and Pathogenesis of Diabetic Nephropathy
Gunter Wolf, … Fuad N. Ziyadeh, in Seldin and Giebisch’s The Kidney (Fourth Edition), 2008
REGRESSION
One would assume that the morphological alterations of advanced diabetic nephropathy (e.g. glomerulosclerosis, interstitial fibrosis) are not reversible and represent a oneway road to ESRD. Experimental (32) and clinical studies (66) show, however, that this pessimistic scenario is not necessarily true. Several studies indicate that aggressive blood pressure control with agents that interfere with the RAAS leads to remission of overt proteinuria. Fioretto and colleagues performed serial renal biopsy in eight patients with type 1 diabetes and nephropathy who had undergone a successful pancreas transplantation (66). These investigators found that the morphological alterations of diabetic nephropathy, including increased GBM thickness and mesangial matrix expansion, decreased 10 years after receiving the pancreas transplant. The data clearly demonstrate that the sustained euglycemia can reverse the development of diabetic nephropathy, but this process takes time. In addition, Perkins et al. (180) showed that the onset of sustained microalbuminuria does not imply inexorably progressive nephropathy, at least not in patients with type 1 diabetes. This study provides indirect evidence that aggressive management aiming at various risk factors could lead to remission of albuminuria. Since no renal biopsies were performed in this study, it remained unproven whether morphological changes of diabetic nephropathy were also improved. Although the molecular mechanisms surrounding regression are currently incompletely understood, it is possible that induction of metalloproteinases that may degrade the deposited extracellular matrix play a central role in this process. Nevertheless, there is light at the end of the tunnel and a better understanding of the complex pathophysiology of diabetic nephropathy will likely improve a multipronged approach to induce regression.
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Socio-economic and environmental assessment of concentrating solar power systems
Natalia CaldésYolanda Lechón, in Concentrating Solar Power Technology (Second Edition), 2021
5.4.1 Environmental impacts projections
The evolution of the GHG and other emissions over time is evaluated in the work performed in the NEEDS project (Viebahn et al., 2011). When assessing the emissions of future configurations of CSP power plants, a clear reduction is observed showing an ‘environmental learning’ of the technology. The three development scenarios: very optimistic, optimistic–realistic, and pessimistic scenarios refer to different assumptions on the anticipated penetration of the technology into the energy market reaching an installed capacity in 2050 of 1000 GW, 405 GW, and 120 GW, respectively. In these scenarios the prevailing CSP technology differs. Greenhouse gas emissions show a large reduction throughout the scenario development. The reason is the reduction of salt used in the different storage systems. Concrete storage or PCM storage based power plants performs better than the current molten salt based ones. The results show a continuous optimization from the ‘pessimistic’ to the ‘very optimistic’ scenario as well as over time.
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27th European Symposium on Computer Aided Process Engineering
Kathleen B. Aviso, … Raymond R. Tan, in Computer Aided Chemical Engineering, 2017
4.1 Reducing Emission through Pollution Control Technologies
This case study considers the selection of pollution control technologies for the reduction in hydrogen fluoride emission in the production of clay bricks such that the emission reduction target is met at the lowest cost. The data used for this case study was obtained from Kantardgi et al. (2006). The data for the emissions reduction technologies are shown in Table 1. Each pollution control technology i is able to reduce the emission of hydrogen fluoride by Ri and has a corresponding capital cost of Ci.
Table 1. Emission reduction potential and capital costs of emission technologies
| Option | Technology Option | % Reduction (Ri) | %Ri Average | Capital Cost in (× 1000 US$) (Ci) | Maximum Capital Cost (× 1000 US$) |
|---|---|---|---|---|---|
| 1 | Modifying the time-temperature profile | 30 – 60 | 45 | 37.8 | 37.8 |
| 2 | Reducing the airflow through the kiln | 30 – 80 | 55 | 37.8 – 151.2 | 151.2 |
| 3 | Increasing the turbulence in the preheat zone | 0 – 50 | 25 | 37.8 – 189 | 189 |
| 4 | Increasing the interaction between the product and the flue gas | 30 – 90 | 60 | 94.5 | 94.5 |
| 5 | Utilizing the flue gas | 30 – 60 | 45 | 3.78 | 3.78 |
| 6 | Additives fluoride reactive compound limestone | 0 – 80 | 40 | 3.78 – 189 | 189 |
| 7 | Dry bed limestone scrubber | 95 | 95 | 226.8 – 945 | 945 |
| 8 | Dry cloth filter scrubber | 95 | 95 | 756 – 1,323 | 1,323 |
| 9 | Wet scrubber | 95 | 95 | 226.8 – 1,323 | 1,323 |
Tan (2007) solved the same case study using the average values of emission reduction potential and the maximum possible capital cost to achieve a minimum emission reduction of 90% (Y = 0.90); this solution is used as Scenario 1 here. This result is compared with the most pessimistic scenario (Scenario 2) where the technologies are assumed to perform with the lowest emission reduction and at the highest capital cost and the most optimistic scenario (Scenario 3) where the technologies perform at the highest emission reduction and the lowest capital cost. The results show that the selection of technologies varies with each scenario. Scenario 1 is able to reduce the emissions by 90% at a cost of US$ 249,480 and selecting technologies 2, 4 and 5. The most optimistic scenario can reach an emission reduction of practically 100% at a cost of US$ 306,180 and selects pollution technologies 1 to 6. Alternatively, the most pessimistic scenario achieves an emission reduction of 90% with an associated cost of US$ 532,980 and selects technologies 1, 2, 4, 5 and 6.
The problem is further analyzed using a Target Oriented Robust Optimization (TORO) model and Monte Carlo simulation in order to identify a robust combination of technologies which takes into consideration the risks associated with the uncertainties in cost and in emission reduction.
The results are summarized in Table 2 where the costs are reported in thousand US$. The parameter % P corresponds to the probability of constraint achievement, while % X corresponds to the emission reduction achieved.
Table 2. Results of TORO optimization as a function of robustness index (θ) for Case 1
The TORO formulation simultaneously considers the existing uncertainties in the cost and emission reduction potential. Based on the results summarized in Table 2, the best solution is to select technologies 1 to 6 since it achieves an emission reduction of 98 %. This solution corresponds to the robustness index of 0.50 to 0.80 and corresponds to the shaded cells found in Table 2. Furthermore, the performance of this solution is expected to have an average cost below the expected cost target level if uncertainties are considered and that constraints will be met to a probability of 80 %.
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Magnitude Coding
Olivier Rance, … Pierre Lemaître-Auger, in RCS Synthesis for Chipless RFID, 2017
4.3.4 Partial conclusion – tags with ground planes
A complete study has been realized to assess the feasibility and the potential gain offered by magnitude coding in the context of chipless RFID. From a comparative study, the simplest way to control the magnitude has been determined. This approach, based on the polarization mismatch between the tag and the antennas, is easy to implement in practice because it only consists of modifying the orientation of the resonators individually, which does not add any particular difficulty when designing the tag. Based on a mostly pessimistic scenario, we estimate a 15-bit coding capacity for a tag made up of four frequency-coded resonators. Magnitude coding has made it possible to increase the coding capacity by 9 bits. It has been shown that the presence of a reference scatterer included in the tag makes it possible to realize measurements with a minimalist calibration process and without depending on the read range.
One limiting aspect that has not been addressed is the influence of the absence of knowledge beforehand of the orientation of the tag in relation to the reader. However, it is theoretically possible to find this information using indirect approaches by implementing them either at the level of the reader or at the level of the tag. For example, an interesting approach consists of comparing the response of two reference resonators that have different, known orientations.
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Case Studies Worldwide
Susan Hanson, … Simon D. Rundle, in Coastal Risk Management in a Changing Climate, 2015
Flooding
SLR induces a shift of the PDF such that higher values are more probable. Hence, it can be deduced that logically the maximum flooding elevation will rise in all the beaches. The distortion of the PDFs are associated mainly to changes in mean sea level, increasing the probability of exceedance of a given beach level. As an example, Figure 7.109 shows the PDF of coastal flooding in Sardinero 2 under the present climate conditions, the moderate change (SLR = +0.2 m), the high change (SLR = +0.4 m), and the pessimistic scenario (SLR = +1 m).
Figure 7.109. PDF of coastal flooding in Sardinero two for the different scenarios of sea-level rise: the present conditions (dark line), moderate change for year 2050 (+0.2 m), high change for year 2080 (+0.4 m), and pessimistic scenario for year 2100 (+1 m).
Besides, the representative parameters (location, scale, and shape) of the GEV distribution for the six beaches and the scenarios analyzed are summarized in Table 7.75.
TABLE 7.75. Summary of the Location, Scale, and Shape Parameters of the GEV Distributions for the Six Beaches Analyzed and Scenarios Proposed
| Location Parameter (μ) | Shape Parameter (ε) | Scale Parameter (Ψ) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Present climate | +0.2 | +0.4 | +1 | Present climate | +0.2 | +0.4 | +1 | Present climate | +0.2 | +0.4 | +1 | |
| Sardinero 2 | 7.81 | 8.01 | 8.21 | 8.81 | −0.25 | −0.25 | −0.25 | −0.25 | 0.6 | 0.6 | 0.6 | 0.6 |
| Sardinero 1 | 7.72 | 7.92 | 8.12 | 8.72 | −0.26 | −0.26 | −0.26 | −0.26 | 0.35 | 0.35 | 0.35 | 0.35 |
| Loredo | 8.62 | 8.82 | 9.02 | 9.62 | −0.25 | −0.25 | −0.25 | −0.25 | 0.43 | 0.43 | 0.43 | 0.43 |
| Somo | 8.08 | 8.28 | 8.48 | 9.08 | −0.24 | −0.24 | −0.24 | −0.24 | 0.38 | 0.38 | 0.38 | 0.38 |
| Puntal | 7.38 | 7.58 | 7.78 | 8.38 | −0.28 | −0.28 | −0.28 | −0.28 | 0.3 | 0.3 | 0.3 | 0.3 |
| Peligros | 6.59 | 6.79 | 6.99 | 7.59 | −0.33 | −0.33 | −0.33 | −0.33 | 0.22 | 0.22 | 0.22 | 0.22 |
The flooding analysis in the inner bay has been carried out using the pragmatic approach described in section 7.9.3.4. The scenarios summarized in Table 7.76 that combine extreme flooding levels with relative SLR projections have been used to assess the flooding in Santander Bay.
TABLE 7.76. Summary of Flooding Scenarios
| Scenario | Year of Return Period | Flooding Level (cm) | Relative Sea-Level Rise (cm) | Total Sea Level | Horizon Year |
|---|---|---|---|---|---|
| A | 50 | 256 | 20 | 276 | 2050 |
| B | 50 | 256 | 40 | 296 | 2080 |
| C | 50 | 256 | 100 | 356 | 2080 |
| D | 200 | 276 | 20 | 296 | 2050 |
| E | 200 | 276 | 40 | 316 | 2080 |
| F | 200 | 276 | 100 | 376 | 2080 |
Figure 7.110 shows the flooding levels associated with a return period of 50 years and an SLR of +1 m (scenario C in Table 7.76). As can be seen in this figure, several areas will be affected by flooding, such as various areas of the Cubas sea inlet (see Figure 7.110(c)). These areas are currently reclaimed, but in the past belonged to the intertidal area of the estuary. Other areas affected belong to Alday marshes (see Figure 7.110(a)). At present, these marshes are regulated hydrodynamically by means of a system of sluices (see Figure 7.110(b)).
Figure 7.110. Different areas affected by flood level in Santander Bay for scenario C.
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Uncertainty Issues in Biomass-Based Production Chains
Şebnem Yılmaz Balaman, in Decision-Making for Biomass-Based Production Chains, 2019
5.2.2.2 Scenario Analyses
Scenario analysis is conducted, to analyze the impacts of possible future events on the system performance by taking into account several alternative outcomes, i.e., scenarios, and to present different options for future development paths resulting in varying outcomes and corresponding implications. Scenario analysis is the process of forecasting the expected value of a performance indicator, given a time period, occurrence of different situations, and related changes in the values of system parameters under an uncertain environment. Scenario analysis can be used to estimate the behavior of the system in response to an unexpected event, and may be utilized to explore the changes in system performance, in a theoretical best-case (optimistic) or worst-case (pessimistic) scenario. The occurrence probability and possible impact of a scenario should be considered in tandem to develop a strategic plan base on scenario analysis results. The major aim is, to analyze the results of the more extreme outcomes (with high probability and/or more severe impacts), to determine the investment strategy.
In design and management of biomass-based production chains, a decision-maker might use scenario analysis to estimate the impacts of several possible scenarios regarding changes in bio-fuel sale prices (increased, reduced, or constant prices), on the performance of the chain. Another analysis may depend on governmental strategies on incentivizing production from renewable sources or specific incentives for carbon sequestering operations. Different incentive policies may be considered to evaluate the behavior and performance of the production chain under changing financial and economic circumstances. The subsets of each of the possibilities and the correlations between these subsets may be taken into account, and the scenario-weighted expected profitability of the production chain may be calculated.
The complexity of the problem, and the existence of stakeholders and related conflicting objectives in a supply chain, may make the scenario analysis a challenging practice. It may be difficult to forecast future events and corresponding impacts and assign probabilities to them. The system may need to be modeled by capturing possible fluctuations within a single scenario or possible correlations between multiple scenarios, which make the analysis further complex.
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24th European Symposium on Computer Aided Process Engineering
Chinedu O. Okoli, Thomas A. AdamsII, in Computer Aided Chemical Engineering, 2014
4.2 Economic results
These results are intuitive, as the feedstock cost makes up a major percentage of the variable operating cost while the mixed alcohols co-product makes up almost half of the products. In order to consider the effects of multiple parameters which change at the same time, different scenarios in which the most significant parameters vary simultaneously are considered as shown in Table 3. The results show that in the “optimistic” to “pessimistic” scenario range of 0.55 — 1.17 $/L the process remains competitive, especially in comparison to ABE-derived butanol prices which range from 0.59 $/L (Kumar et al., 2012) to 1.05 $/L (Qureshi et al., 2013). An important assumption in this study is the alcohol synthesis catalyst CO-conversion of 40 %. This value is in line with the National Renewable Energy Laboratory target of greater than 50 % CO-conversion for alcohol synthesis catalysts, achievable from future research advances (Phillips et al., 2007). However the catalyst used in this study has a CO-conversion of 8.5 % (Herman, 2000), a value that results in an MBSP of 1.60 $/L which is unlikely to be competitive. Furthermore, the base case MBSP result of 0.84 $/L in comparison to the gasoline price of 0.82 $/Lbeq is intuitive, as the MBSP should be worse than the gasoline price except for high crude oil price situations. Thus this process provides a method of producing 2nd generation biofuels at only a small premium over petroleum-derived gasoline, assuming the achievement of the target alcohol synthesis catalyst CO-conversion. In addition, it is important to note that the lignocellulose biomass-to-butanol ABE process has only been demonstrated at the laboratory scale, and thus the wide range of prices for ABE-derived butanol is highly uncertain as it is unlikely to be better than gasoline.
Table 3. Impact of different economic scenarios on the MBSP
| Scenarios – Parameter Values Considered | Very Optimistic | Optimistic | Base Case | Pessimistic | Very Pessimistic |
|---|---|---|---|---|---|
| Internal Rate of Return | 5 | 7.5 | 10 | 12.5 | 15 |
| Feedstock costs ($/dry t) | 60 | 68 | 75 | 83 | 90 |
| Mixed Alcohol value ($/L) | 0.85 | 0.77 | 0.69 | 0.62 | 0.54 |
| Total Depreciable Capital | 230 | 279 | 328 | 377 | 426 |
| Resulting MBSP ($/L) | 0.29 | 0.55 | 0.84 | 1.17 | 1.54 |
Table 2. Breakdown of capital cost
| Capital cost calculations | $ Million |
|---|---|
| Total Installed Equipment | |
| Cost | 214 |
| Total Indirect Cost | 114 |
| Total Depreciable Capital | 328 |
| Royalties | 7 |
| Land | 6 |
| Fixed Capital Investment | 341 |
| Working Capital | 17 |
| Total Capital Investment | 358 |
Figure 2. Sensitivity of the MBSP (base case of 0.84 $/L) to changes in key parameters
Finally, an area to consider in future research is the impact of cheaper feedstocks, such as switchgrass and wheat straw, on the thermochemical biobutanol MBSP. These feedstocks will have different performance metrics, as they will form different syngas compositions with undetermined ripple effects through the process which will have to be evaluated.
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26th European Symposium on Computer Aided Process Engineering
Anvitha Kandiraju, … Ignacio E. Grossmann, in Computer Aided Chemical Engineering, 2016
5 Illustrative Example
The proposed formulation is tested on an a small instance from the air separation industry. This instance has two facilities of the leader and three facilities of the independent suppliers, satisfying demands of 10 markets over a period of 30 quarters (7.5 years). Facilities from the leader have a capacity of 75,000 tons/period and 20,000 tons/period. Independent suppliers have capacities of 100,000 tons/period, 70,000 tons/period and 20,000 tons/period. The capacity expansion limit for each plant is 9000 tons/period. All the capacities are shared between two products with production ratios of 15-25% for product-1 and 75-85% for product-2 with respect to the overall production. There are three demand scenarios that can occur: pessimistic scenario in which the demand drops from 132,700 tons/period to 100,000 tons/period; nominal case where the demand increases from 132,700 tons/period to 161,000 tons/period; and an optimistic case in which the demand further increases from 132,700 tons/period to 256,600 tons/period. Discount rate of 3% is used. Fixed and operating costs increase with time, which are not elaborated here due to space restrictions. We plan the capacity strategy for the leader under the above mentioned conditions.
We consider a stochastic programming model and the equivalent deterministic case in order to compare the performance of the models. The deterministic case is obtained by taking an average over the three demand scenarios. The expansion strategy obtained from the deterministic case is enforced on the stochastic model to analyze the impact of ignoring demand uncertainty. The results are presented in Table 1.
Table 1. Comparison of the results for the deterministic and the stochastic formulations
| Term in objective function | Deterministic solution | Stochastic solution | Deterministic solution under uncertainty |
|---|---|---|---|
| Revenue (MM$): | 1,548 | 1,331 | 1,460 |
| New facilities (MM$): | 0 | 0 | 0 |
| Maintenance (MM$): | 127 | 127 | 127 |
| Expansion (MM$): | 187 | 96 | 187 |
| Production (MM$): | 660 | 568 | 625 |
| Transportation (MM$): | 130 | 120 | 124 |
| NPV (MM$): | 444 | 420 | 397 |
It can be seen from Table1 that the deterministic model gives higher NPV for an average demand case. However, when deterministic solutions are enforced in the face of uncertainties, the model gives lower expected NPV ($397MM) in comparison to the stochastic model ($420MM).
The deterministic model makes aggressive capacity expansion decisions while the stochastic programming model is more conservative. This is because of the high probability of pessimistic and nominal demand scenarios. Considering all demand scenarios in the formulation mitigates the risk associated to demand uncertainties.
The MILP reformulations were implemented in GAMS 24.4.6 and solved using CPLEX 12.6.2.0. The computational statistics for the models are presented in Table 2. The stochastic model has increased size compared to the deterministic case because of the additional scenarios. The increase involves more constraints and continuous variables, while the number of discrete variables remains the same as they are planning decisions which are shared for all scenarios.
Table 2. Model statistics for the proposed formulations
| Model statistic | Deterministic model | Stochastic model |
|---|---|---|
| Number of constraints: | 6,412 | 18,586 |
| Number of continuous variables: | 8,246 | 24,261 |
| Number of binary variables: | 146 | 146 |
| Solution time (s): | 49 | 55 |
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Pessimistic Scenarios
John F. Shroder, in Natural Resources in Afghanistan, 2014
Abstract
Pessimistic scenarios for Afghanistan’s future rest particularly on the prospects for ongoing incessant war in the country because of a long list of such things as Pashtun cultural characteristics; neo-environmental determinism with a harsh physical environment leading to environmental and developmental problems; charismatic or “mad” mullahs who encourage bad behaviors; strong ethnic patchworks leading to ethnic cleansing, and the like; repeated foreign invasions; Afghan xenophobia; endemic corruption; land-ownership disputes; Islamicist desire for endless jihad; decades of war, destroyed educational systems, reduced capacity, widespread illiteracy, drug culture, and the purdah culture wherein valuable women are excluded from normal and useful problem solving. In addition are the paranoia, insecurity, and inability of nearby Pakistan to gain the upper hand over the ISI-driven and protected Taliban insurgency enjoying largely unmolested safe haven there, coupled with similar but not as extreme difficulties with fanatically religious Iran as well: the existing environmental basket case of Afghanistan only contributes further fuel to the pessimism. None of these problems is sufficient by itself to keep Afghanistan down, but in aggregate, they seem to have been enough to spoil the country up to now.
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Renewable energy integration as an alternative to the traditional ground-source heat pump system
Cristina Sáez Blázquez, … Diego González-Aguilera, in Energy Services Fundamentals and Financing, 2021
5.5.1.3 CO2 emission factor
The last variable considered in the sensitivity analysis is the CO2 emission factor. Observing Table 5.10, the expected emission factor is 0.399. As in the previous cases, optimistic and pessimistic scenarios have also been analyzed. Thus this factor has been reduced and increased in a 15%, obtaining for the optimistic situation an emission factor of 0.339 and 0.459 for the pessimistic one. Fig. 5.12 shows how the sensitivity to the increase or reduction of the emission factor is approximately the same in both systems. However, as in the previous cases, the sensitivity of the conventional system is higher compared to the suggested one.
Figure 5.12. Sensitivity analysis to the variation of the CO2 emission factor. Op, optimistic scenario; Ex, expected scenario; Pe, pessimistic scenario.
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Pathophysiology and Pathogenesis of Diabetic Nephropathy
Gunter Wolf, … Fuad N. Ziyadeh, in Seldin and Giebisch’s The Kidney (Fourth Edition), 2008
REGRESSION
One would assume that the morphological alterations of advanced diabetic nephropathy (e.g. glomerulosclerosis, interstitial fibrosis) are not reversible and represent a oneway road to ESRD. Experimental (32) and clinical studies (66) show, however, that this pessimistic scenario is not necessarily true. Several studies indicate that aggressive blood pressure control with agents that interfere with the RAAS leads to remission of overt proteinuria. Fioretto and colleagues performed serial renal biopsy in eight patients with type 1 diabetes and nephropathy who had undergone a successful pancreas transplantation (66). These investigators found that the morphological alterations of diabetic nephropathy, including increased GBM thickness and mesangial matrix expansion, decreased 10 years after receiving the pancreas transplant. The data clearly demonstrate that the sustained euglycemia can reverse the development of diabetic nephropathy, but this process takes time. In addition, Perkins et al. (180) showed that the onset of sustained microalbuminuria does not imply inexorably progressive nephropathy, at least not in patients with type 1 diabetes. This study provides indirect evidence that aggressive management aiming at various risk factors could lead to remission of albuminuria. Since no renal biopsies were performed in this study, it remained unproven whether morphological changes of diabetic nephropathy were also improved. Although the molecular mechanisms surrounding regression are currently incompletely understood, it is possible that induction of metalloproteinases that may degrade the deposited extracellular matrix play a central role in this process. Nevertheless, there is light at the end of the tunnel and a better understanding of the complex pathophysiology of diabetic nephropathy will likely improve a multipronged approach to induce regression.
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Socio-economic and environmental assessment of concentrating solar power systems
Natalia CaldésYolanda Lechón, in Concentrating Solar Power Technology (Second Edition), 2021
5.4.1 Environmental impacts projections
The evolution of the GHG and other emissions over time is evaluated in the work performed in the NEEDS project (Viebahn et al., 2011). When assessing the emissions of future configurations of CSP power plants, a clear reduction is observed showing an ‘environmental learning’ of the technology. The three development scenarios: very optimistic, optimistic–realistic, and pessimistic scenarios refer to different assumptions on the anticipated penetration of the technology into the energy market reaching an installed capacity in 2050 of 1000 GW, 405 GW, and 120 GW, respectively. In these scenarios the prevailing CSP technology differs. Greenhouse gas emissions show a large reduction throughout the scenario development. The reason is the reduction of salt used in the different storage systems. Concrete storage or PCM storage based power plants performs better than the current molten salt based ones. The results show a continuous optimization from the ‘pessimistic’ to the ‘very optimistic’ scenario as well as over time.
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27th European Symposium on Computer Aided Process Engineering
Kathleen B. Aviso, … Raymond R. Tan, in Computer Aided Chemical Engineering, 2017
4.1 Reducing Emission through Pollution Control Technologies
This case study considers the selection of pollution control technologies for the reduction in hydrogen fluoride emission in the production of clay bricks such that the emission reduction target is met at the lowest cost. The data used for this case study was obtained from Kantardgi et al. (2006). The data for the emissions reduction technologies are shown in Table 1. Each pollution control technology i is able to reduce the emission of hydrogen fluoride by Ri and has a corresponding capital cost of Ci.
Table 1. Emission reduction potential and capital costs of emission technologies
| Option | Technology Option | % Reduction (Ri) | %Ri Average | Capital Cost in (× 1000 US$) (Ci) | Maximum Capital Cost (× 1000 US$) |
|---|---|---|---|---|---|
| 1 | Modifying the time-temperature profile | 30 – 60 | 45 | 37.8 | 37.8 |
| 2 | Reducing the airflow through the kiln | 30 – 80 | 55 | 37.8 – 151.2 | 151.2 |
| 3 | Increasing the turbulence in the preheat zone | 0 – 50 | 25 | 37.8 – 189 | 189 |
| 4 | Increasing the interaction between the product and the flue gas | 30 – 90 | 60 | 94.5 | 94.5 |
| 5 | Utilizing the flue gas | 30 – 60 | 45 | 3.78 | 3.78 |
| 6 | Additives fluoride reactive compound limestone | 0 – 80 | 40 | 3.78 – 189 | 189 |
| 7 | Dry bed limestone scrubber | 95 | 95 | 226.8 – 945 | 945 |
| 8 | Dry cloth filter scrubber | 95 | 95 | 756 – 1,323 | 1,323 |
| 9 | Wet scrubber | 95 | 95 | 226.8 – 1,323 | 1,323 |
Tan (2007) solved the same case study using the average values of emission reduction potential and the maximum possible capital cost to achieve a minimum emission reduction of 90% (Y = 0.90); this solution is used as Scenario 1 here. This result is compared with the most pessimistic scenario (Scenario 2) where the technologies are assumed to perform with the lowest emission reduction and at the highest capital cost and the most optimistic scenario (Scenario 3) where the technologies perform at the highest emission reduction and the lowest capital cost. The results show that the selection of technologies varies with each scenario. Scenario 1 is able to reduce the emissions by 90% at a cost of US$ 249,480 and selecting technologies 2, 4 and 5. The most optimistic scenario can reach an emission reduction of practically 100% at a cost of US$ 306,180 and selects pollution technologies 1 to 6. Alternatively, the most pessimistic scenario achieves an emission reduction of 90% with an associated cost of US$ 532,980 and selects technologies 1, 2, 4, 5 and 6.
The problem is further analyzed using a Target Oriented Robust Optimization (TORO) model and Monte Carlo simulation in order to identify a robust combination of technologies which takes into consideration the risks associated with the uncertainties in cost and in emission reduction.
The results are summarized in Table 2 where the costs are reported in thousand US$. The parameter % P corresponds to the probability of constraint achievement, while % X corresponds to the emission reduction achieved.
Table 2. Results of TORO optimization as a function of robustness index (θ) for Case 1
The TORO formulation simultaneously considers the existing uncertainties in the cost and emission reduction potential. Based on the results summarized in Table 2, the best solution is to select technologies 1 to 6 since it achieves an emission reduction of 98 %. This solution corresponds to the robustness index of 0.50 to 0.80 and corresponds to the shaded cells found in Table 2. Furthermore, the performance of this solution is expected to have an average cost below the expected cost target level if uncertainties are considered and that constraints will be met to a probability of 80 %.
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Magnitude Coding
Olivier Rance, … Pierre Lemaître-Auger, in RCS Synthesis for Chipless RFID, 2017
4.3.4 Partial conclusion – tags with ground planes
A complete study has been realized to assess the feasibility and the potential gain offered by magnitude coding in the context of chipless RFID. From a comparative study, the simplest way to control the magnitude has been determined. This approach, based on the polarization mismatch between the tag and the antennas, is easy to implement in practice because it only consists of modifying the orientation of the resonators individually, which does not add any particular difficulty when designing the tag. Based on a mostly pessimistic scenario, we estimate a 15-bit coding capacity for a tag made up of four frequency-coded resonators. Magnitude coding has made it possible to increase the coding capacity by 9 bits. It has been shown that the presence of a reference scatterer included in the tag makes it possible to realize measurements with a minimalist calibration process and without depending on the read range.
One limiting aspect that has not been addressed is the influence of the absence of knowledge beforehand of the orientation of the tag in relation to the reader. However, it is theoretically possible to find this information using indirect approaches by implementing them either at the level of the reader or at the level of the tag. For example, an interesting approach consists of comparing the response of two reference resonators that have different, known orientations.
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Case Studies Worldwide
Susan Hanson, … Simon D. Rundle, in Coastal Risk Management in a Changing Climate, 2015
Flooding
SLR induces a shift of the PDF such that higher values are more probable. Hence, it can be deduced that logically the maximum flooding elevation will rise in all the beaches. The distortion of the PDFs are associated mainly to changes in mean sea level, increasing the probability of exceedance of a given beach level. As an example, Figure 7.109 shows the PDF of coastal flooding in Sardinero 2 under the present climate conditions, the moderate change (SLR = +0.2 m), the high change (SLR = +0.4 m), and the pessimistic scenario (SLR = +1 m).
Figure 7.109. PDF of coastal flooding in Sardinero two for the different scenarios of sea-level rise: the present conditions (dark line), moderate change for year 2050 (+0.2 m), high change for year 2080 (+0.4 m), and pessimistic scenario for year 2100 (+1 m).
Besides, the representative parameters (location, scale, and shape) of the GEV distribution for the six beaches and the scenarios analyzed are summarized in Table 7.75.
TABLE 7.75. Summary of the Location, Scale, and Shape Parameters of the GEV Distributions for the Six Beaches Analyzed and Scenarios Proposed
| Location Parameter (μ) | Shape Parameter (ε) | Scale Parameter (Ψ) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Present climate | +0.2 | +0.4 | +1 | Present climate | +0.2 | +0.4 | +1 | Present climate | +0.2 | +0.4 | +1 | |
| Sardinero 2 | 7.81 | 8.01 | 8.21 | 8.81 | −0.25 | −0.25 | −0.25 | −0.25 | 0.6 | 0.6 | 0.6 | 0.6 |
| Sardinero 1 | 7.72 | 7.92 | 8.12 | 8.72 | −0.26 | −0.26 | −0.26 | −0.26 | 0.35 | 0.35 | 0.35 | 0.35 |
| Loredo | 8.62 | 8.82 | 9.02 | 9.62 | −0.25 | −0.25 | −0.25 | −0.25 | 0.43 | 0.43 | 0.43 | 0.43 |
| Somo | 8.08 | 8.28 | 8.48 | 9.08 | −0.24 | −0.24 | −0.24 | −0.24 | 0.38 | 0.38 | 0.38 | 0.38 |
| Puntal | 7.38 | 7.58 | 7.78 | 8.38 | −0.28 | −0.28 | −0.28 | −0.28 | 0.3 | 0.3 | 0.3 | 0.3 |
| Peligros | 6.59 | 6.79 | 6.99 | 7.59 | −0.33 | −0.33 | −0.33 | −0.33 | 0.22 | 0.22 | 0.22 | 0.22 |
The flooding analysis in the inner bay has been carried out using the pragmatic approach described in section 7.9.3.4. The scenarios summarized in Table 7.76 that combine extreme flooding levels with relative SLR projections have been used to assess the flooding in Santander Bay.
TABLE 7.76. Summary of Flooding Scenarios
| Scenario | Year of Return Period | Flooding Level (cm) | Relative Sea-Level Rise (cm) | Total Sea Level | Horizon Year |
|---|---|---|---|---|---|
| A | 50 | 256 | 20 | 276 | 2050 |
| B | 50 | 256 | 40 | 296 | 2080 |
| C | 50 | 256 | 100 | 356 | 2080 |
| D | 200 | 276 | 20 | 296 | 2050 |
| E | 200 | 276 | 40 | 316 | 2080 |
| F | 200 | 276 | 100 | 376 | 2080 |
Figure 7.110 shows the flooding levels associated with a return period of 50 years and an SLR of +1 m (scenario C in Table 7.76). As can be seen in this figure, several areas will be affected by flooding, such as various areas of the Cubas sea inlet (see Figure 7.110(c)). These areas are currently reclaimed, but in the past belonged to the intertidal area of the estuary. Other areas affected belong to Alday marshes (see Figure 7.110(a)). At present, these marshes are regulated hydrodynamically by means of a system of sluices (see Figure 7.110(b)).
Figure 7.110. Different areas affected by flood level in Santander Bay for scenario C.
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Uncertainty Issues in Biomass-Based Production Chains
Şebnem Yılmaz Balaman, in Decision-Making for Biomass-Based Production Chains, 2019
5.2.2.2 Scenario Analyses
Scenario analysis is conducted, to analyze the impacts of possible future events on the system performance by taking into account several alternative outcomes, i.e., scenarios, and to present different options for future development paths resulting in varying outcomes and corresponding implications. Scenario analysis is the process of forecasting the expected value of a performance indicator, given a time period, occurrence of different situations, and related changes in the values of system parameters under an uncertain environment. Scenario analysis can be used to estimate the behavior of the system in response to an unexpected event, and may be utilized to explore the changes in system performance, in a theoretical best-case (optimistic) or worst-case (pessimistic) scenario. The occurrence probability and possible impact of a scenario should be considered in tandem to develop a strategic plan base on scenario analysis results. The major aim is, to analyze the results of the more extreme outcomes (with high probability and/or more severe impacts), to determine the investment strategy.
In design and management of biomass-based production chains, a decision-maker might use scenario analysis to estimate the impacts of several possible scenarios regarding changes in bio-fuel sale prices (increased, reduced, or constant prices), on the performance of the chain. Another analysis may depend on governmental strategies on incentivizing production from renewable sources or specific incentives for carbon sequestering operations. Different incentive policies may be considered to evaluate the behavior and performance of the production chain under changing financial and economic circumstances. The subsets of each of the possibilities and the correlations between these subsets may be taken into account, and the scenario-weighted expected profitability of the production chain may be calculated.
The complexity of the problem, and the existence of stakeholders and related conflicting objectives in a supply chain, may make the scenario analysis a challenging practice. It may be difficult to forecast future events and corresponding impacts and assign probabilities to them. The system may need to be modeled by capturing possible fluctuations within a single scenario or possible correlations between multiple scenarios, which make the analysis further complex.
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24th European Symposium on Computer Aided Process Engineering
Chinedu O. Okoli, Thomas A. AdamsII, in Computer Aided Chemical Engineering, 2014
4.2 Economic results
These results are intuitive, as the feedstock cost makes up a major percentage of the variable operating cost while the mixed alcohols co-product makes up almost half of the products. In order to consider the effects of multiple parameters which change at the same time, different scenarios in which the most significant parameters vary simultaneously are considered as shown in Table 3. The results show that in the “optimistic” to “pessimistic” scenario range of 0.55 — 1.17 $/L the process remains competitive, especially in comparison to ABE-derived butanol prices which range from 0.59 $/L (Kumar et al., 2012) to 1.05 $/L (Qureshi et al., 2013). An important assumption in this study is the alcohol synthesis catalyst CO-conversion of 40 %. This value is in line with the National Renewable Energy Laboratory target of greater than 50 % CO-conversion for alcohol synthesis catalysts, achievable from future research advances (Phillips et al., 2007). However the catalyst used in this study has a CO-conversion of 8.5 % (Herman, 2000), a value that results in an MBSP of 1.60 $/L which is unlikely to be competitive. Furthermore, the base case MBSP result of 0.84 $/L in comparison to the gasoline price of 0.82 $/Lbeq is intuitive, as the MBSP should be worse than the gasoline price except for high crude oil price situations. Thus this process provides a method of producing 2nd generation biofuels at only a small premium over petroleum-derived gasoline, assuming the achievement of the target alcohol synthesis catalyst CO-conversion. In addition, it is important to note that the lignocellulose biomass-to-butanol ABE process has only been demonstrated at the laboratory scale, and thus the wide range of prices for ABE-derived butanol is highly uncertain as it is unlikely to be better than gasoline.
Table 3. Impact of different economic scenarios on the MBSP
| Scenarios – Parameter Values Considered | Very Optimistic | Optimistic | Base Case | Pessimistic | Very Pessimistic |
|---|---|---|---|---|---|
| Internal Rate of Return | 5 | 7.5 | 10 | 12.5 | 15 |
| Feedstock costs ($/dry t) | 60 | 68 | 75 | 83 | 90 |
| Mixed Alcohol value ($/L) | 0.85 | 0.77 | 0.69 | 0.62 | 0.54 |
| Total Depreciable Capital | 230 | 279 | 328 | 377 | 426 |
| Resulting MBSP ($/L) | 0.29 | 0.55 | 0.84 | 1.17 | 1.54 |
Table 2. Breakdown of capital cost
| Capital cost calculations | $ Million |
|---|---|
| Total Installed Equipment | |
| Cost | 214 |
| Total Indirect Cost | 114 |
| Total Depreciable Capital | 328 |
| Royalties | 7 |
| Land | 6 |
| Fixed Capital Investment | 341 |
| Working Capital | 17 |
| Total Capital Investment | 358 |
Figure 2. Sensitivity of the MBSP (base case of 0.84 $/L) to changes in key parameters
Finally, an area to consider in future research is the impact of cheaper feedstocks, such as switchgrass and wheat straw, on the thermochemical biobutanol MBSP. These feedstocks will have different performance metrics, as they will form different syngas compositions with undetermined ripple effects through the process which will have to be evaluated.
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26th European Symposium on Computer Aided Process Engineering
Anvitha Kandiraju, … Ignacio E. Grossmann, in Computer Aided Chemical Engineering, 2016
5 Illustrative Example
The proposed formulation is tested on an a small instance from the air separation industry. This instance has two facilities of the leader and three facilities of the independent suppliers, satisfying demands of 10 markets over a period of 30 quarters (7.5 years). Facilities from the leader have a capacity of 75,000 tons/period and 20,000 tons/period. Independent suppliers have capacities of 100,000 tons/period, 70,000 tons/period and 20,000 tons/period. The capacity expansion limit for each plant is 9000 tons/period. All the capacities are shared between two products with production ratios of 15-25% for product-1 and 75-85% for product-2 with respect to the overall production. There are three demand scenarios that can occur: pessimistic scenario in which the demand drops from 132,700 tons/period to 100,000 tons/period; nominal case where the demand increases from 132,700 tons/period to 161,000 tons/period; and an optimistic case in which the demand further increases from 132,700 tons/period to 256,600 tons/period. Discount rate of 3% is used. Fixed and operating costs increase with time, which are not elaborated here due to space restrictions. We plan the capacity strategy for the leader under the above mentioned conditions.
We consider a stochastic programming model and the equivalent deterministic case in order to compare the performance of the models. The deterministic case is obtained by taking an average over the three demand scenarios. The expansion strategy obtained from the deterministic case is enforced on the stochastic model to analyze the impact of ignoring demand uncertainty. The results are presented in Table 1.
Table 1. Comparison of the results for the deterministic and the stochastic formulations
| Term in objective function | Deterministic solution | Stochastic solution | Deterministic solution under uncertainty |
|---|---|---|---|
| Revenue (MM$): | 1,548 | 1,331 | 1,460 |
| New facilities (MM$): | 0 | 0 | 0 |
| Maintenance (MM$): | 127 | 127 | 127 |
| Expansion (MM$): | 187 | 96 | 187 |
| Production (MM$): | 660 | 568 | 625 |
| Transportation (MM$): | 130 | 120 | 124 |
| NPV (MM$): | 444 | 420 | 397 |
It can be seen from Table1 that the deterministic model gives higher NPV for an average demand case. However, when deterministic solutions are enforced in the face of uncertainties, the model gives lower expected NPV ($397MM) in comparison to the stochastic model ($420MM).
The deterministic model makes aggressive capacity expansion decisions while the stochastic programming model is more conservative. This is because of the high probability of pessimistic and nominal demand scenarios. Considering all demand scenarios in the formulation mitigates the risk associated to demand uncertainties.
The MILP reformulations were implemented in GAMS 24.4.6 and solved using CPLEX 12.6.2.0. The computational statistics for the models are presented in Table 2. The stochastic model has increased size compared to the deterministic case because of the additional scenarios. The increase involves more constraints and continuous variables, while the number of discrete variables remains the same as they are planning decisions which are shared for all scenarios.
Table 2. Model statistics for the proposed formulations
| Model statistic | Deterministic model | Stochastic model |
|---|---|---|
| Number of constraints: | 6,412 | 18,586 |
| Number of continuous variables: | 8,246 | 24,261 |
| Number of binary variables: | 146 | 146 |
| Solution time (s): | 49 | 55 |
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