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At least 397 records · Page 22

Benefit Analysis of CO 2 Delivery Options for Offshore Storage or Enhanced Oil Recovery

The analysis presented in this report evaluates the benefits of CO₂ offshore transport via pipeline or ship within the GOM. It takes a top-down framework to estimate the costs. First, this analysis designed a reduced-order model (ROM) based on the cash flows in the FECM/NETL CO₂ Transport Cost Model (also known as CO2_T_COM). The ROM takes capital expenses (CAPEX) and operating expenses (OPEX) to calculate the CO₂ breakeven price based on the cash flows. Second, this analysis developed regression models utilizing published data from other analyses to estimate CAPEX and OPEX. Since the ROM is a simplified cash flow calculation, it is easy to exchange the core regression models to estimate various costs. The ROM and regression models provided a framework that can be easily used by other researchers, decision-makers, operators, and regulators. The objective of this analysis is to assess the CO₂ breakeven cost range for pipeline and ship transport of captured CO₂ given the CO₂ source and storage reservoir located in the GOM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Security Evaluation of Smart Cards and Secure Tokens: Benefits and Drawbacks for Reducing Supply Chain Risks of Nuclear Power Plants

The supply chain attack pathway is being increasingly used by adversaries to bypass security controls and gain unauthorized access to sensitive networks and equipment (e.g., Critical Digital Assets). Cyber-attacks targeting supply chain generally aim to compromise the environments, products, or services of vendors and suppliers to inject, add, or substitute authentic software and hardware with malicious elements. These malicious elements are deemed to be authentic as they arise from the vendor or supplier (i.e., the supply chain). This research aims to leverage findings and assumptions made from the previous report to determine the security benefits and drawbacks of a smart card- based hardware root of trust. Smart cards can provide devices inside Nuclear Power Plants (NPP) with a secure environment to store keys in and perform sensitive operations such as digital signature generation. These abilities can be leveraged to increase supply chain cybersecurity by autonomously providing NPP Licensees with reports on device integrity, authenticity and measurements of executable and non-executable data.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Windfarm Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT)

This report provides technical documentation and background on the newly-developed Wind Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT) software. WOMBAT is an open-source model that can be used to obtain cost estimates for operations and maintenance of land-based or offshore wind power plants. The software was designed to be flexible and modular to allow for implementation of new strategies and technological innovations for wind plant maintenance. WOMBAT uses a process-based simulation approach to model day-to-day operations, repairs, and weather conditions. High-level outputs from WOMBAT, including time-based availability and annual operating costs, are found to agree with published results from other models.

17 WIND ENERGY↗

Cooling Egypt: Cost and benefits of room air conditioner efficiency improvement in Egypt

Egypt is one of the largest countries in the Middle East and North Africa region with a population of a total of 106 million (as of July 2022). Increasing urbanization, population growth, and increasing temperatures will likely continue to drive demand for electricity from air conditioning, with corresponding negative impacts on the peak load, air quality, and greenhouse gas emissions from refrigerant use and energy consumption. Since 2003, Egypt has adopted a standards and labeling program for various appliances, and has improved its room air conditioner (RAC) energy efficiency requirements in 2016 and 2017. However, its market is still dominated by inefficient fixed-speed drive (FSD) RACs due to a price-sensitive market. Seasonal metrics such as Cooling Season Performance Factor (CSPF) measure the energy efficiency of FSD and variable-speed drive (VSD) RACs on the same scale. Leading markets, most notably China, have already adopted a new MEPS in 2020 and 2022, which align largely with the United for Efficiency (U4E) Model Regulations Guidelines. India has also adopted a CSPF metric. Both India and China are now experiencing (1) increased demand and consumption of higher efficiency VSD RACs, as well as (2) a corresponding drop in prices from the economies of scale of production of these higher efficiency RACs. Because China is a leading manufacturer in the global air conditioner (AC) market, its adoption of the model U4E regulations have effectively raised the energy efficiency of the ACs in the global market. To achieve the benefits of taking a similar approach to Egypt’s market, we offer the following recommendations: 1. Adopt a common metric to measure the efficiency of both FSD and VSD RACs 2. Raise the stringency of MEPS to the level of the U4E Model Regulation Guidelines 3. Restructure the labeling program from the “A++” labeling scheme to a simpler A through E or a star-rating program 4. Strengthen the compliance regime governing the Egyptian AC MEPS 5. Assist small and medium AC manufacturers in Egypt to transition manufacturing lines to produce low-cost, high-efficiency VSD RACs. Adopting these recommendations would reduce Egypt’s electricity consumption to 11 TWh in 2030 and 89 TWh in 2050—with corresponding carbon dioxide (CO2) emissions reductions and avoided generation capacity requirements compared to the baseline.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Feasibility and the Benefits of the Advanced Nuclear Fuel Pellet Designs with Radially Varying Fuel Zoning and Burnable Poison Concentration (Final Summary Report)

As part of the work supported by the US Department of Energy (DOE) Office of Nuclear Energy (NE) Gateway for Accelerated Innovation in Nuclear (GAIN) FY 2021 Voucher, Exelon Generation, now Constellation, and Oak Ridge National Laboratory (ORNL) entered into a cooperative research and development agreement (CRADA) to evaluate and assess the feasibility and impact of various conceptual advanced nuclear fuel pellet designs (ANFPDs). The objective of this project was to perform modeling and simulation and analyses using the advanced modeling and simulation capabilities of VERA/BISON, developed by DOE, to determine the viability and benefits of numerous advanced nuclear fuel pellet design concepts in terms of fuel cycle costs, operational safety, and margin improvement. Whereas the detailed coupled neutronic and thermal hydraulic analyses performed using VERA provided in-depth knowledge in terms of fuel cycle performance, the detailed VERA results were used in subsequent fuel performance analyses using BISON. These subsequent analyses focused on several key fuel performance criteria, such as peak fuel centerline temperature (FCT), fission gas release (FGR), gap closure, plenum pressure, and cladding hoop stress. These key fuel performance criteria were analyzed for some of the conceptual fuel designs and were compared with the results obtained for UO 2 fuel. The results provided detailed information to enable better understanding of the performance of the fuel types analyzed. Understanding the advantage of loading these conceptual fuel designs into the core is important not only to Constellation but also to the entire light-water reactor (LWR) fleet in the United States.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Resilience for Advanced Distributed Wind Systems: Identifying the resilience benefits of advanced controls and hybrid systems for distributed wind

Under the Department of Energy (DOE) Wind Energy Technologies Office (WETO), Idaho National Laboratory (INL) has been tasked with defining the resilience benefits of distributed wind systems for the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project. This project is a collaboration between the National Renewable Energy Laboratory (NREL), Sandia National Laboratories (SNL) and Pacific Northwest National Laboratory (PNNL). In the final year of this project, INL is collaborating with the other labs to bring together key results from our previous work on resilience, cybersecurity and risk, distributed wind hybrid systems, and valuation of distributed wind.

17 WIND ENERGY↗

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗

LA100 Equity Strategies. Chapter 8: Equitable Rooftop Solar Access and Benefits

The LA100 Equity Strategies project integrates community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. This chapter focuses on analysis of customer-sited rooftop solar and storage as a means to reduce electricity bills for low- and moderate-income (LMI) households, multifamily building residents, and renters, who traditionally lack access to bill savings from rooftop solar. Specifically, NREL modeled customer-sited solar and storage adoption using the Distributed Generation Market Demand (dGen™)1 model through 2035 and developed scenarios to identify programs or policies that could support equitable access to bill savings from rooftop solar or solar-plus-storage. Scenarios tested include a direct-install program for LMI customers, net metering for LMI customers, and equitable distribution of benefits from installing solar between owners and renters of renter-occupied buildings. Research was guided by input from the community engagement process, and equity strategies are presented in alignment with that guidance.

14 SOLAR ENERGY↗

Spatially Adaptive Tunable Lighting Control System with Expanded Wellness and Energy Saving Benefits

Lighting design is becoming increasingly complex, including active dimming for energy savings and spectral tuning for human wellbeing. Modern commercial lighting control systems are already difficult to use, and maintain, and even with so-called Smart Lighting, optimizing light settings is rapidly exceeding the capabilities of direct human control, limiting the adoption of lighting control systems. The growing importance of Occupancy Centric Controls (OCC) for advanced building management systems can be applied to the development of autonomous lighting system controls needed to drive the adoption of advanced lighting controls for improved adaptive “sculpted illumination” for both greater energy savings and broader human wellbeing perspectives. This project, led by Rensselaer Polytechnic Institute, entitled “Spatially adaptive tunable lighting control system with expanded wellness and energy saving benefits” will develop and test an entirely new platform for automated optimized lighting design and control that requires little or no human engagement, yet contours lighting profiles automatically to minimize lighting energy use. We call this approach to lighting control “dynamic light sculpting” since the right amount of illumination is automatically delivered to occupants in real time. Since the system uses new, privacy-preserving occupant position and pose detection technologies developed by Rensselaer for broad OCC building applications, the control system will analyze how to deliver the right amount of the right type of illumination only where and when it is needed based these OCC platforms. To create these powerful autonomous lighting control platforms, the project will integrate evolving augmented reality (AR) and virtual reality (VR) tools with sophisticated lighting and interior design toolkits to create interactive lighting design and control simulators. Using the quickly growing paradigm of digital twins, these tools will integrate light fixture properties, occupancy sensor data, interior design data, and lighting specifications to accurately visualize how various design concepts interact with simulated yet realistic human activities that occur in commercial office buildings of various types. These advanced digital twin design and simulation tools will be combined with a new class of digitally-programmable LED lighting fixtures that can dynamically change the spectral content and direction of light emission. When fully integrated, the new autonomous lighting control system will take all of the guesswork out of optimizing light quality while minimizing energy consumption. Digital twin tools will simplify the design, installation, commissioning, operation, and maintenance of future energy-efficient lighting systems. It should be possible to reduce lighting energy costs from 40% to 70% with OCC based dynamic light sculpting systems. The work will be led by the Center for Lighting Enabled Systems and Applications (LESA) and the Center for Architectural Science and Ecology (CASE), both at Renssealer Polytechnic Institute; Lumileds, a global leader in the development of advanced LED systems; and HKS, a leading global architecture design firm. This interdisciplinary project team’s experience includes all of the design simulation tools, VR/AR digital twin visualization technology, advanced occupancy sensing technology, and complex control system design capabilities that will revolutionize lighting design and control technology to autonomously deliver high-quality lighting that improves human health and wellbeing while simultaneously maximizing lighting energy savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Quantifying and Valuing Fundamental Characteristics and Benefits of Floating PV Systems

This project undertook the first systematic and comprehensive collection of Floating Photovoltaic (FPV) related techno-ecological data across diverse geographic regions of the United States. It examined FPV performance, assessed potential environmental risks and benefits, and provided data to support the development of research protocols for better understanding the impacts of FPV. As part of this process, we conducted a detailed study of four existing FPV sites and three land-based PV (LPV) sites in Florida and California.

14 SOLAR ENERGY↗

Project No. 5: Evaluating Dredged Materials for Energy Storage Applications with Economic and Carbon Benefits (CRADA Final Report)

The New York Power Authority (NYPA) is committed to supporting the Climate Leadership and Community Protection Act (CLCPA) through its VISION2030 strategic plan. As a clean energy provider, NYPA is seeking to demonstrate leadership in every aspect of its business by taking a comprehensive approach to sustainability management and integrating sustainability principles into day-to-day decision-making. This effort includes planning for climate resilience through projects that mitigate climate risk in our operations and prioritize climate opportunities in our investments. Canal Corporation, a subsidiary of NYPA, is charged with maintaining minimum water depths for navigation in the Cayuga-Seneca, Champlain, Erie and Oswego Canals. In order to do so, an average volume of 280,000 cubic yards of sediment is dredged annually and held in Upland Disposal Sites (UDS) permitted by the New York Department of Environmental Conservation (NYSDEC). The required on-land storage at UDSes are nearing capacity, and disposal opportunities are costly, both economically and environmentally. Novel energy storage technology developed by NREL provides an opportunity for meeting NYPA's need to find reuse options for dredged materials and commitment to providing clean reliable energy. This would also support NYPA's goal of developing 300 MW of utility scale storage and enabling 150 MW of distributed storage by 2030. NREL will consult NYPA on the environmental and economic impact of reusing dredged materials as useful commodities such as energy storage media, construction sand or industrial uses. Test and material characterization methods will be based on current NREL storage material characterization approaches. NREL worked with NYPA on sample preparation, material testing, test results analysis. Test and material characterization methods were based on current NREL storage material characterization approaches. The team analyzed the environmental and economic impact of reusing dredged materials as useful commodities such as energy storage media, construction sand or industrial uses. The test and analysis works have achieved the project goal in characterizing NYPA dredging materials and verifying their various uses including construction sand and thermal energy storage media. Uses of dredging materials as useful materials will bring economic and environmental benefits and avoid disposal costs.

25 ENERGY STORAGE↗

Optimizing Carbon Capture, Transport, and Storage: Overcoming Challenges with Machine Learning and Cost-Benefit Analysis

Carbon Capture, Utilization, and Storage (CCUS) is a critical strategy for reducing CO₂ emissions and mitigating climate change. However, its widespread deployment faces numerous challenges across the capture, transport, and storage phases. These challenges include the technical complexity of predicting subsurface behaviors during CO₂ injection, ensuring long-term storage integrity, optimizing transportation networks, and balancing the economic and environmental trade-offs. Addressing these issues requires an integrated approach combining advanced subsurface modeling with system-level analyses to assess costs, risks, and benefits. This presentation provides an overview of studies conducted by the National Energy Technology Laboratory (NETL) to tackle these challenges. NETL’s efforts encompass cutting-edge research in subsurface fluid behavior machine learning predictions, alongside the development of innovative tools for system optimization and economic evaluation. By bridging technical expertise and strategic analysis, NETL aims to advance the deployment of CCUS technologies to support global decarbonization efforts. Presented at the Carnegie Mellon University CEE IESS Student Seminar October 4, 2024.

Shih, Chung Yan↗

Construction Methodology Transformation for the Benefit of Workforce Development

Construction is a key economic engine driving both national and global economies. While manual, onsite construction methods dominate the U.S. construction industry, a major shift towards offsite methods has been underway due to its efficiency, speed, and potential cost savings. The workforce necessary for offsite construction growth does not exist in its current form because of the focus on onsite methodologies and the lack of exposure to offsite building methods at all levels of a student’s learning journey. The growth of the U.S. construction industry and competitiveness in an increasingly global construction market over the coming decades can only be supported by a dramatic increase in the use of offsite methods, which requires ramping up workforce training for certain skillsets. The goal of Construction Methodology Transformation for the Benefit of Workforce Development was to understand the opportunities and barriers in both education and industry and to identify best practices for offering curriculum and training to educators, industry, and students that would support skills needed for careers in offsite construction. Our team proposed combining three offsite construction workforce development needs: content development, exposure and training, and job placement - under a single Platform model that would increase experience and career opportunities for students and help match them with potential industry members. Through our proposed solution we expected to see: developed offsite curriculum being utilized by educators and students; an increase in the identification of construction technology and offsite construction methods; an average increase in knowledge gain of at least 25% after participation in pilots; better equipped candidates who are prepared for jobs in offsite construction; and a beta workforce development platform that helps build more pathways for students looking for careers in offsite construction. The two pilots included almost 250 students and resulted in an average knowledge gain of 37 percent. Our research has identified areas of opportunity, for both education and industry to make collaborative training programs more efficient and successful. The chosen techniques for this program are extremely effective when both the school and factory have solid processes and cultures in place to accept students into training programs. This project serves as an important stepping stone to industrywide collaboration to move workforce development for offsite construction forward across the country. With continued collaboration programs like this can provide much needed early exposure and training in offsite construction and we can begin to fill important positions for the future of construction.

99 GENERAL AND MISCELLANEOUS↗

Hybrid Powered Command Trailers Cost-Benefit Analysis Tool: User Guide and Examples

U.S. Forest Service (USFS) wildfire base camps use portable power for electrical needs, including yurts and trailers from which logistics staff work during the incident. These yurts and trailers are conventionally powered by portable diesel generators. Hybrid portable power systems consisting of a combination of solar photovoltaics (PV), battery energy storage systems (BESS), and/or backup diesel generators have been used in recent years and were piloted by the National Technology and Development Program (NTDP) on incidents in fall 2024 as part of NTDP's Portable Power Project. As part of that project, this work included the development of two Excel-based tools and two reports explaining the tools. The first tool, the Incident Energy Systems Model, is an Excel-based tool that models the power output of hybrid portable power systems powering yurts and/or trailers at fire camps over a typical day. The associated report (published separately) outlines a user guide for the model and walks through two scenarios. The two scenarios are 1) trailers powered by rooftop solar PV, batteries, and a back-up diesel generator, and 2) trailers powered by ground mount solar PV, batteries, and a back-up diesel generator. The second tool is a high-level cost-benefit analysis of the same two types of portable power systems, and is location independent.

14 SOLAR ENERGY↗

Quantifying and Optimizing the Energy Benefits of Mass Timber Construction

The International Mass Timber Alliance (IMTA) is a global organization of industry leaders, engineers, scientists, and associations dedicated to advancing mass timber construction. Its mission is to generate and disseminate scientific data supporting the development of standardized construction and energy efficient practices that promote the adoption of mass timber worldwide. IMTA collaborated with Oak Ridge National Laboratory (ORNL) to leverage ORNL’s expertise in building envelope modeling and testing to evaluate how mass timber construction can reduce peak heating and cooling demand, lower overall energy use, and improve resilience during power outages. A previous study of 80 mass timber buildings in Finland found measured energy use up to 50% lower than predicted by simulation. This project aimed to validate and extend those findings for U.S. buildings through analytical modeling, laboratory testing, and full-scale building evaluations. The research focused on the thermal performance of low-embodied-energy wall assemblies, such as cross-laminated timber (CLT) panels and log walls, with particular attention to the effects of thermal inertia on indoor comfort and energy performance. While mass timber’s structural and fire-resistance properties are well documented, its whole-building thermal behavior has received limited attention. Field data, simulation results, and resilience testing from this study will inform future modeling practices, design guidelines, and construction practices by quantifying the unique thermal and demand-flexibility benefits of mass timber construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Benefits of Energy Storage for Washington, D.C.: Analysis for the Department of Energy and Environment

This report analyzes the potential for using energy storage to create energy savings for residents of Washington, D.C. in light of recent increases in energy market prices. It describes the role of energy storage in avoiding market costs, quantifies the specific benefits that could be achieved with energy storage deployments in Washington, D.C., and then presents case studies of how utilities and other states have created programs to achieve cost savings with energy storage.

25 ENERGY STORAGE↗

Artificial Intelligence in Nuclear Safeguards; Evaluating Safeguards and Security Risks and Benefits for Advanced and Small Modular Reactor Deployments

Rapidly growing interest in advanced and small modular reactor (A/SMR) technologies presents challenges as well as opportunities for implementing international safeguards and security. A/SMR deployments are expected to be more numerous, more geographically dispersed, and more varied in their designs, placing new demands on the data systems and analytical tools used to support oversight (Alberti et al., 2023; Canadian Nuclear Safety Commission et al., 2024). Because of this variability, the importance and reliance on data systems for A/SMR deployments is expected to be higher than for previous reactor generations. Artificial Intelligence and Machine Learning (AI/ML) offer potential capabilities to address the high variability inherent in A/SMR technology. The beneficiaries of AI-assisted tools include facility operators, government regulators, IAEA inspectors, and A/SMR vendors. This report analyzes how AI/ML-assisted technologies can strengthen the implementation of IAEA safeguards and security measures. It also identifies AI-assisted tools to strengthen operator, facility, and regulator knowledge management practices and examines the potential risks AI/ML-based tools may introduce to IAEA safeguards and security efforts. It concludes with a set of hypothetical, standards-style requirements for AI/ML systems used in safeguards contexts, grounded in an inspector-centric view of system verification. Despite the potential benefits of AI/ML systems, understanding potential intentional and unintentional failure modes is critical for ensuring adequate protection of nuclear materials and facilities. Unique features of A/SMRs including sealed cores, remote and novel paradigms of operation, off-site reactor fabrication, novel fuel forms, and varied refueling requirements, introduce challenges for traditional safeguards technological approaches (Pensado et al., 2024; Federation of American Scientists, 2025). AI/ML systems deployed to address these challenges may introduce new risks requiring systematic evaluation rooted in both AI-specific risk frameworks, such as the NIST AI Risk Management Framework (NIST AI RMF), and established cyber risk management standards such as NIST SP 800-30 (National Institute of Standards and Technology [NIST], 2023; NIST, 2012).

97 MATHEMATICS AND COMPUTING↗

Evaluating the Benefits of Bayesian Hierarchical Methods for Analyzing Heterogeneous Environmental Datasets: A Case Study of Marine Organic Carbon Fluxes

Large compilations of heterogeneous environmental observations are increasingly available as public databases, allowing researchers to test hypotheses across datasets. Statistical complexities arise when analyzing compiled data due to unbalanced spatial sampling, variable environmental context, mixed measurement techniques, and other reasons. Hierarchical Bayesian modeling is increasingly used in environmental science to describe these complexities, however few studies explicitly compare the utility of hierarchical Bayesian models to simpler and more commonly applied methods. Here we demonstrate the utility of the hierarchical Bayesian approach with application to a large compiled environmental dataset consisting of 5,741 marine vertical organic carbon flux observations from 407 sampling locations spanning eight biomes across the global ocean. We fit a global scale Bayesian hierarchical model that describes the vertical profile of organic carbon flux with depth. Profile parameters within a particular biome are assumed to share a common deviation from the global mean profile. Individual station-level parameters are then modeled as deviations from the common biome-level profile. The hierarchical approach is shown to have several benefits over simpler and more common data aggregation methods. First, the hierarchical approach avoids statistical complexities introduced due to unbalanced sampling and allows for flexible incorporation of spatial heterogeneitites in model parameters. Second, the hierarchical approach uses the whole dataset simultaneously to fit the model parameters which shares information across datasets and reduces the uncertainty up to 95% in individual profiles. Third, the Bayesian approach incorporates prior scientific information about model parameters; for example, the non-negativity of chemical concentrations or mass-balance, which we apply here. We explicitly quantify each of these properties in turn. We emphasize the generality of the hierarchical Bayesian approach for diverse environmental applications and its increasing feasibility for large datasets due to recent developments in Markov Chain Monte Carlo algorithms and easy-to-use high-level software implementations.

54 ENVIRONMENTAL SCIENCES↗