Computational Methods in Environmental and Resource Economics

2019 ◽  
Vol 11 (1) ◽  
pp. 59-82 ◽  
Author(s):  
Yongyang Cai
Keyword(s):  
Computational Methods ◽  
Real Option ◽  
Resource Economics ◽  
Bilevel Optimization ◽  
Curse Of Dimensionality ◽  
Computational Method ◽  
Computational Techniques ◽  
Deterministic Models ◽  
Environmental And Resource Economics ◽  
Dynamic Stochastic

Computational methods are required to solve problems without closed-form solutions in environmental and resource economics. Efficiency, stability, and accuracy are key elements for computational methods. This review discusses state-of-the-art computational methods applied in environmental and resource economics, including optimal control methods for deterministic models, advances in value function iteration and time iteration for general dynamic stochastic problems, nonlinear certainty equivalent approximation, robust decision making, real option analysis, bilevel optimization, solution methods for continuous time problems, and so on. This review also clarifies the so-called curse of dimensionality, and discusses some computational techniques such as approximation methods without the curse of dimensionality and time-dependent approximation domains. Many existing economic models use simplifying and/or unrealistic assumptions with an excuse of computational feasibility, but these assumptions might be able to be relaxed if we choose an efficient computational method discussed in this review.

Bayesian Estimation of DSGE Models

2015 ◽  
Author(s):  
Edward P. Herbst ◽  
Frank Schorfheide
Keyword(s):  
Monte Carlo ◽  
Sequential Monte Carlo ◽  
Likelihood Function ◽  
Academic Research ◽  
Dynamic Stochastic General Equilibrium ◽  
Computational Techniques ◽  
Dsge Models ◽  
Monte Carlo Techniques ◽  
Dynamic Stochastic ◽  
Theoretical Foundations

Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. The book is essential reading for graduate students, academic researchers, and practitioners at policy institutions.

Computational Methods for Socio-Computer Interaction

2018 ◽  
Author(s):  
Wai-Tat Fu ◽  
Mingkun Gao ◽  
Hyo Jin Do
Keyword(s):  
Computational Methods ◽  
User Interfaces ◽  
Social Processes ◽  
Computational Techniques ◽  
Special Focus ◽  
Design Features ◽  
Social Phenomena ◽  
Online Social Media ◽  
Social Opinions ◽  
Computer Interaction

From the Arab Spring to presidential elections, various forms of online social media, forums, and networking platforms have been playing increasing significant roles in our societies. These emerging socio-computer interactions demand new methods of understanding how various design features of online tools may moderate the percolation of information and gradually shape social opinions, influence social choices, and moderate collective action. This chapter starts with a review of the literature on the different ways technologies impact social phenomena, with a special focus on theories that characterize how social processes are moderated by various design features of user interfaces. It then reviews different theory-based computational methods derived from these theories to study socio-computer interaction at various levels. Specific examples of computational techniques are reviewed to illustrate how they can be useful for influencing social processes for various purposes. The chapter ends with how future technologies should be designed to improve socio-computer interaction.

Computational Methods to Support Brittle Fracture Assessment of PSVs Involving Autorefrigeration

2015 ◽  
Author(s):  
Kannan Subramanian ◽  
Jorge Penso ◽  
Harbi Pordal
Keyword(s):  
Brittle Fracture ◽  
Computational Methods ◽  
Cost Effective ◽  
Liquid Hydrocarbon ◽  
Computational Method ◽  
Metal Temperature ◽  
Relief Valve ◽  
Sensitivity Studies ◽  
Fracture Assessment ◽  
Cfd Method

Pressure safety relief valve (PSV) operation generally leads to cooling of the valve itself and the piping connected to the PSV. The temperatures may reach values below the minimum design metal temperature (MDMT) of the valve, and therefore the valve needs to be assessed for brittle fracture susceptibility. Simplistic determination of the minimum metal temperature in the valve may disqualify these valves during the brittle fracture assessments (BFA). Replacement may be time consuming and may not be cost effective. In such circumstances, a sophisticated and more representative BFA approach involving the use of computational fluid dynamics (CFD) followed by finite element method (FEM) based stress analysis which may be further followed by fracture mechanics can be adopted based on the concepts defined in ASME/API 579. The accuracy of the BFA depends on the accuracy of each of the computational method involved in the assessment. Among all the computational methods, CFD poses significant challenge. The low temperature may have been caused due to Joule-Thompson effect or auto-refrigeration. While Joule-Thompson effect can be best captured with easy to implement and robust CFD methods, auto-refrigeration involving adiabatic flashing which causes additional complexity and requires multiple sensitivity studies performed to determine the accuracy of the CFD approach. In this paper, an overview of the computational methods used in the brittle fracture assessment of PSVs is presented. Specific CFD method details are provided for PSV involving the flashing of liquid hydrocarbon to vapor is presented in the form of a case study derived from downstream industry application.

scholarly journals Computational Methods for the Identification of Molecular Targets of Toxic Food Additives. Butylated Hydroxytoluene as a Case Study

Molecules ◽  
2020 ◽  
Vol 25 (9) ◽  
pp. 2229 ◽  
Author(s):  
Valentina Tortosa ◽  
Valentina Pietropaolo ◽  
Valentina Brandi ◽  
Gabriele Macari ◽  
Andrea Pasquadibisceglie ◽  
...  
Keyword(s):  
Computational Methods ◽  
Food Additives ◽  
Daily Intake ◽  
Experimental Studies ◽  
Butylated Hydroxytoluene ◽  
Computational Techniques ◽  
Toxicological Effects ◽  
Ligand Interactions ◽  
Toxic Food

Butylated hydroxytoluene (BHT) is one of the most commonly used synthetic antioxidants in food, cosmetic, pharmaceutical and petrochemical products. BHT is considered safe for human health; however, its widespread use together with the potential toxicological effects have increased consumers concern about the use of this synthetic food additive. In addition, the estimated daily intake of BHT has been demonstrated to exceed the recommended acceptable threshold. In the present work, using BHT as a case study, the usefulness of computational techniques, such as reverse screening and molecular docking, in identifying protein–ligand interactions of food additives at the bases of their toxicological effects has been probed. The computational methods here employed have been useful for the identification of several potential unknown targets of BHT, suggesting a possible explanation for its toxic effects. In silico analyses can be employed to identify new macromolecular targets of synthetic food additives and to explore their functional mechanisms or side effects. Noteworthy, this could be important for the cases in which there is an evident lack of experimental studies, as is the case for BHT.

scholarly journals Estimation of Time-Course Core Temperature and Water Loss in Realistic Adult and Child Models with Urban Micrometeorology Prediction

2019 ◽  
Vol 16 (24) ◽  
pp. 5097 ◽  
Author(s):  
Toshiki Kamiya ◽  
Ryo Onishi ◽  
Sachiko Kodera ◽  
Akimasa Hirata
Keyword(s):  
Core Temperature ◽  
Water Loss ◽  
Urban Areas ◽  
Time Course ◽  
The Body ◽  
Computational Method ◽  
Heat Index ◽  
Computational Techniques ◽  
Ambient Conditions ◽  
Urban Micrometeorology

Ambient conditions may change rapidly and notably over time in urban areas. Conventional indices, such as the heat index and wet bulb globe temperature, are useful only in stationary ambient conditions. To estimate the risks of heat-related illness, human thermophysiological responses should be followed for ambient conditions in the time domain. We develop a computational method for estimating the time course of core temperature and water loss by combining micrometeorology and human thermal response. We firstly utilize an urban micrometeorology prediction to reproduce the environment surrounding walkers. The temperature elevations and sweating in a standard adult and child are then estimated for meteorological conditions. With the integrated computational method, we estimate the body temperature and thermophysiological responses for an adult and child walking along a street with two routes (sunny and shaded) in Tokyo on 7 August 2015. The difference in the core temperature elevation in the adult between the two routes was 0.11 °C, suggesting the necessity for a micrometeorology simulation. The differences in the computed body core temperatures and water loss of the adult and child were notable, and were mainly characterized by the surface area-to-mass ratio. The computational techniques will be useful for the selection of actions to manage the risk of heat-related illness and for thermal comfort.

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