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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Managing weather- and market price-related financial risks in algal biofuel production

Large-scale algae production has garnered interest due to its potential as a biofuel feedstock. Previous research assessing the profitability of algae products has been mostly based on values averaged over time, but algae production and resulting financial returns exhibit significant variability due to weather and fluctuations in selling prices for algae-based products. In other sectors, producers often reduce weather- and market price-related financial risk with financial instruments such as insurance, but little research has been performed on the design of insurance products to protect algae producers. Furthermore, this study develops a novel index-based insurance instrument that pays-out during unfavorable weather and market conditions, then explores the instrument's effectiveness, combined with a cash reserve, in reducing revenue stream variability for an algae producer. Results indicate that a biophysically based index-insurance product tailored to the specific financial risks in algae production can reduce variability in net revenues and can do so at a lower cost than relying solely on cash reserves, the most common financial risk management tool. Assessing the performance of index-insurance in algae production is particularly timely given the passage of the 2018 Farm Bill, which newly opens opportunities for the USDA to provide crop insurance to algae producers.

09 BIOMASS FUELS↗
DOE OSTI2024

Resilient water infrastructure partnerships in institutionally complex systems face challenging supply and financial risk tradeoffs

Abstract As regions around the world invest billions in new infrastructure to overcome increasing water scarcity, better guidance is needed to facilitate cooperative planning and investment in institutionally complex and interconnected water supply systems. This work combines detailed water resource system ensemble modeling with multiobjective intelligent search to explore infrastructure investment partnership design in the context of ongoing canal rehabilitation and groundwater banking in California. Here we demonstrate that severe tradeoffs can emerge between conflicting goals related to water supply deliveries, partnership size, and the underlying financial risks associated with cooperative infrastructure investments. We show how hydroclimatic variability and institutional complexity can create significant uncertainty in realized water supply benefits and heterogeneity in partners’ financial risks that threaten infrastructure investment partnership viability. We demonstrate how multiobjective intelligent search can design partnerships with substantially higher water supply benefits and a fraction of the financial risk compared to status quo planning processes. This work has important implications globally for efforts to use cooperative infrastructure investments to enhance the climate resilience and financial stability of water supply systems.

Science & Technology - Other Topics↗
DOE OSTI2022

Hypofractionated Radiation Therapy for Breast Cancer: Financial Risk and Expenditures in the United States, 2008 to 2017

Rising cancer care expenditures and technological advancement of shorter radiation therapy regimens have drawn significant attention to the use of hypofractionated radiation therapy in clinical care. We examine the costs of hypofractionated whole breast irradiation (HF-WBI) compared with conventional whole breast irradiation (CF-WBI) in the United States and investigate the influences of patient characteristics and commercial insurance on HF-WBI use.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2000

Managing schedule and financial risk in a faster, better, cheaper development

The X2000 Program is a technology development program that will provide next generation avionics for missions to deep space. The goal of the X2000 Program is to develop revolutionary flight and ground systems which can be replicated by missions at a low cost, affording timely new science and mission opportunities to investigators and institutions.

risk finance schedule↗
DOE OSTI2026

Demand response event simulator and risk-aware bidding tool for industrial customers

Incentive Based Demand Response (IBDR) program participation delivers financial benefits to the consumers and resiliency benefits to the electricity grid. Effectively participating in these programs as an industrial consumer requires bidding strategies that balance financial risk with operational constraints. Existing bidding tools tend not to fully incorporate stochastic IBDR event modeling, program specific baseline and payment/penalty calculations, or demand reduction process control schemes that account for the cascading impacts of shutdown in complex facilities. Here, this work presents an IBDR event simulator and risk-aware bidding framework tool integrating three key components: a flexible, parameterized demand response event generator that rigorously accounts for program structures and stochasticity, a demand response operational simulation model that generates explicit control strategies for load reduction, and a Monte Carlo simulator to evaluate financial risk for varied capacity bids. A case study at a wastewater treatment plant participating in PG&E's Capacity Bidding Program demonstrates the framework's utility. In the peak capacity price month of August, optimal bidding by the wastewater treatment plant nets a mean IBDR benefit of $101,000 (67% of the August electricity bill) with 0.4% probability of a financial loss. This framework enables industrial operators to make informed bidding decisions, negotiate better program terms with demand response load aggregators, and analyze energy flexibility investments at their facilities. Ultimately, this work reduces participation barriers in IBDR programs and supports the broader goal of enhancing grid reliability and renewable energy integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Book Chapter: Small Modular Reactors

Small Modular Reactors (SMRs) have been a very promising development in nuclear power over the last two decades. SMRs are defined as nuclear reactors with a power output of less than 300 MWe. This is in comparison to gigawatt-size reactors, which can have electrical output of 1000–1500 MWe or more. This chapter will consist of two major sections. The first will be a detailed summary of the small modular reactor designs being proposed around the world. This section will focus on those that are the furthest along in their development, but will also include some information about the wide variety of proposed designs that require significant research and development. The second part will be a discussion of the remaining challenges to the adoption of SMRs as a major energy source. SMRs are not a new concept, but they do represent a new vision for an older concept. These reactors have the potential to become a major source of energy in the near future. The development of small, modular designs can help promote the adoption of nuclear energy by reducing upfront costs, reducing the financial risk associated with nuclear power, and the barriers to entry. However, the adoption of SMRs is not without challenges. Regulatory and licensing changes to address the unique benefits and concerns associated with SMRs will continue to be a challenge as regulators adapt to the unique features emerging from the design process. The development of new instrumentation and control systems is an ongoing issue. And economics is possibly the most significant challenge, with high construction costs, cheap natural gas, and government subsidies, combining to result in significant financial risk associated with adopting nuclear generation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Quantifying Uncertainty of Deep Reinforcement Learning Based Decision Making for Operations and Maintenance of Nuclear Power Plant

This paper summarizes research that integrates condition monitoring and prognostics with decision making for nuclear power plant operations and maintenance. As part of this research, we have developed an online asset management tool to help reduce life-cycle maintenance and repair costs. Using the latest advancements in condition monitoring, supply chain analytics, and deep reinforcement learning, we have created a predictive maintenance tool that can optimize the maintenance and spare-part management of a repairable nuclear system. To demonstrate these methods, preliminary studies were conducted on a simple, representative maintenance system undergoing a stochastic degradation process that requires repairs or replacement to continue operation. Through Monte Carlo simulations, we were able to reduce maintenance spending by approximately 50% compared to optimized, time-based maintenance strategies. Not only does the decision maker reduce the average life-cycle costs, it also minimizes the chance of high cost scenarios, lowering the variance of the expected cost distributions, and reducing overall financial risk. Furthermore, this work also studies the ability of the decision maker to handle various levels of noise from observation uncertainty. By introducing uncertainty into the decision-making process, we have quantified the robustness and resiliency of the decision maker, as well as identified necessary levels of observability to demonstrate cost effectiveness.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Stabilization of light-induced effects in Si modules for IEC 61215 design qualification

Standardized testing of commercial photovoltaic modules is widely used around the world and decreases risks of module failures. Such testing also reduces financial risks for module manufacturers and customers. This work examines the expected impact of certain defects in silicon (Si) modules during standardized accelerated testing. Specifically, the behavior of boron-oxygen (BO) light-induced degradation (LID) and light- and elevated temperature-induced degradation (LeTID) are simulated during some of the stress tests in IEC 61215. LID and LeTID reaction rates at qualification temperatures are estimated from earlier published data. It is demonstrated the BO-related LID may cause some false positives and false negatives when IEC 61215 tests are performed as prescribed in the 2016 published version. Possible stabilization steps to avoid these false results are suggested. State changes for the defects causing LeTID occur much more slowly than those causing BO LID, and therefore LeTID is predicted to have a lesser impact on the IEC 61215 stress tests results.

14 SOLAR ENERGY↗
DOE OSTI2024

Stochastic Distribution Control Theory-Its Potential Application in Risk Management in Financial Systems

Stochastic Distribution Control (SDC) theory [1], originated by the author in 1996, aims at developing modeling and control strategies for dynamic and non-Gaussian stochastic systems by controlling the shape of the probability density functions of some concerned variables and parameters in stochastic systems. It generalizes the capability of standard stochastic differential equations and can therefore be applied to generic non-Gaussian systems. Since it was established in 1996, it has found a wide spectrum of applications in non-Gaussian stochastic system control, data mining, filtering and optimization for uncertain systems. In this short opinion article, discussions will be made on potential applications of SDC theory to financial systems in terms of risk analysis and management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Quantifying Uncertainty in PV Energy Estimates Final Report

Uncertainty in PV energy estimates is "one of the most critical areas of lack of understanding" according to independent engineers, financiers, PV model developers, and other industry stakeholders. The primary problem is a lack of rigorous, transparent, widely accepted methods for quantifying uncertainty in energy production estimates. Uncertainty in energy production estimates arises from variability of the solar resource, inexact PV performance models and their parameters, and system reliability considerations. Uncertainty in annual energy production is frequently calculated for larger projects in order to quantify financial risk. Key statistics for energy, such as the P-values "P50" and "P90" (the annual energy values that are exceeded in future years with 50\% and 90\% probability, respectively) are used by financing institutions to calculate the repayment risk for the project. The current methods to estimate these statistics are typically proprietary, specialized, and involve significant post-processing of commercial performance model results. This black-box approach leads to inconsistent P-value estimates from different parties, which reduces investors' confidence in the results. Since the financial community bases its risk assessment on these estimates, reduced confidence increases perceived project risk, and consequently financing costs. The goal of this project was to establish a set of best practices for quantifying uncertainty in energy production estimates, including identifying what sources of uncertainty must be considered with clear definitions and metrics, determining which sources are the biggest drivers of uncertainty, and providing a computationally efficient framework for combining different sources of uncertainty that is flexible enough to accommodate substitutions of data or methods when better information is available. We engaged a wide set of stakeholders to ensure industry endorsement and adoption, and leveraged complementary projects investigating individual sources of uncertainty in great detail, as well as others' work that started down this path.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
DOE OSTI2023

Economic impact and risk analysis of integrating sustainable aviation fuels into refineries

The growth of the aviation industry coupled with its dependence on energy dense, liquid fuels has brought sustainable aviation fuel (SAF) research to the forefront of the biofuels community. Petroleum refineries will need to decide how to satisfy the projected increase in jet fuel demand with either capital investments to debottleneck current operations or by integrating bio-blendstocks. This work seeks to compare jet production strategies on a risk-adjusted, economic performance basis using Monte-Carlo simulation and refinery optimization models. Additionally, incentive structures aiming to de-risk initial SAF production from the refiner’s perspective are explored. Results show that market sensitive incentives can reduce the financial risks associated with producing SAFs and deliver marginal abatement costs ranging between 136-182 $/Ton-CO2e.

09 BIOMASS FUELS↗
NASA NTRS1990

US development and commercialization of a North American mobile satellite service

U.S. policies promoting applications and commercialization of space technology for the 'benefit of mankind,' and emphasis on international competitiveness, formed the basis of NASA's Mobile Satellite (MSAT) R&D and user experiments program to develop a commercial U.S. Mobile Satellite Service. Exemplifying this philosophy, the MSAT program targets the reduction of technical, regulatory, market, and financial risks that inhibit commercialization. The program strategy includes industry and user involvement in developing and demonstrating advanced technologies, regulatory advocacy, and financial incentives to industry. Approximately two decades of NASA's satellite communications development and demonstrations have contributed to the emergence of a new multi-billion dollar industry for land, aeronautical, and maritime mobile communications via satellite. NASA's R&D efforts are now evolving from the development of 'enabling' ground technologies for VHF, UHF, and L-Band mobile terminals, to Ka-Band terminals offering additional mobility and user convenience.

Arnold, Ray J.↗
NASA NTRS2001

Automated Theorem Proving in High-Quality Software Design

The amount and complexity of software developed during the last few years has increased tremendously. In particular, programs are being used more and more in embedded systems (from car-brakes to plant-control). Many of these applications are safety-relevant, i.e. a malfunction of hardware or software can cause severe damage or loss. Tremendous risks are typically present in the area of aviation, (nuclear) power plants or (chemical) plant control. Here, even small problems can lead to thousands of casualties and huge financial losses. Large financial risks also exist when computer systems are used in the area of telecommunication (telephone, electronic commerce) or space exploration. Computer applications in this area are not only subject to safety considerations, but also security issues are important. All these systems must be designed and developed to guarantee high quality with respect to safety and security. Even in an industrial setting which is (or at least should be) aware of the high requirements in Software Engineering, many incidents occur. For example, the Warshaw Airbus crash, was caused by an incomplete requirements specification. Uncontrolled reuse of an Ariane 4 software module was the reason for the Ariane 5 disaster. Some recent incidents in the telecommunication area, like illegal "cloning" of smart-cards of D2GSM handies, or the extraction of (secret) passwords from German T-online users show that also in this area serious flaws can happen. Due to the inherent complexity of computer systems, most authors claim that only a rigorous application of formal methods in all stages of the software life cycle can ensure high quality of the software and lead to real safe and secure systems. In this paper, we will have a look, in how far automated theorem proving can contribute to a more widespread application of formal methods and their tools, and what automated theorem provers (ATPs) must provide in order to be useful.

Schumann, Johann↗