SEARCH · Engineering Papers

Results for “Economic Model”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,657 records · Page 92

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Evaluating advanced nuclear fission technologies for future decarbonized power grids

Advanced nuclear fission, which encompasses various innovative nuclear reactor designs, could contribute to the decarbonization of the United States electricity sector. However, little is known about how cost-competitive these reactors would be compared to other technologies, or about which aspects of their designs offer the most value to a decarbonized power grid. We employ an electricity system optimization model and a case study of a decarbonized U.S. Eastern Interconnection circa 2050 to generate initial indicators of future economic value for advanced reactors and the sensitivity of future value to various design parameters, the availability of competing technologies, and the underlying policy environment. These results can inform long-term cost targets and guide near-term innovation priorities, investments, and reactor design decisions. We find that advanced reactors should cost $\$5.7$–$\$7.3$/W to gain an initial market share (assuming 30 year asset life and 3.5 %–6.5 % real weighted average cost of capital), while those that include thermal storage in their designs can cost up to $\$6.0$/W–$\$7.7$/W (not including cost of storage). Since the marginal value of advanced fission reactors declines as market penetration increases, break-even costs fall ~32 % at 100 GW of cumulative capacity and ~51 % at 300 GW. Additionally, policies that provide investment tax credits for nuclear energy create the most favorable environment for advanced nuclear fission. In conclusion, these findings can inform near-term resource allocation decisions by stakeholders, innovators and investors working in the energy technology sector.

Capacity expansion↗

DOE OSTI2025

Implications of point defect accumulation on UO 2 thermal conductivity and fission gas release under accelerated fuel irradiation

Evaluation of thermal properties is a crucial factor for nuclear fuel performance. During reactor operation, the accumulation of fission products and irradiation-induced lattice defects are responsible for degradation in thermal conductivity. Consequently, it affects fuel temperature and fission gas release (FGR) among other Multiphysics processes important for economics and safety analysis. We analyze the implications of point defects (PD) accumulation described using a rate theory (RT) Model on lattice thermal conductivity of UO 2 . Here, we demonstrate that fission rate-dependent point defect concentrations have the largest impact on in-pile thermal conductivity in the periphery of light water reactor fuels below a temperature threshold governed by the migration barrier of defects. Our analysis provides a mechanistic description of this phenomena which current fuel performance codes treat empirically. The reduction of thermal conductivity in the low -temperature rim region acts as additional thermal resistance and leads to a temperature notably larger than suggested by Lucuta thermal conductivity correlation. These effects are anticipated to have notable impacts when fuels are exposed to accelerated radiation. The impact of such point defect-informed treatment of thermal conductivity on fuel performance is evaluated by a detailed analysis of fission gas behavior and its release. We consider several models capturing different stages of fission gas bubble evolution and fission gas release (FGR). Finally, a new fission rate-dependent correction to the Lucuta correlation is proposed. The results show a significant reduction in thermal conductivity at the fuels’ periphery and an increase in fuel centerline temperature specifically at low burnups. Ultimately a modified LC shows a higher FGR compared to the original LC, while the acceleration process results in a reduction in overall FGR.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Biochemical Conversion of Lignocellulosic Biomass to Hydrocarbon Fuels and Products: 2022 State of Technology and Future Research

The annual State of Technology (SOT) assessment is a key activity for biochemical platform research. It allows the impact of research progress (both directly achieved in-house at the National Renewable Energy Laboratory [NREL] and indirectly extrapolated from available public data) to be quantified in terms of economic improvements in the overall cellulosic biofuel production process for a particular conversion pathway. As such, initial benchmarks can be established for currently demonstrated performance and progress can be tracked toward out-year goals to ultimately demonstrate cost-competitive biofuel technology. Building upon efforts to progress NREL's biochemical platform R&D work toward ultimate 2030 goals to demonstrate less than $2.50/gallon gasoline equivalent (GGE) fuel selling prices, experimental and techno-economic analysis (TEA) activities have primarily focused on "advanced" biochemical processing strategies to fuels and coproducts, guided by TEA modeling to highlight key barriers and priorities toward achieving this goal across a number of potential bioconversion pathways. The purpose of the present effort is to benchmark the latest experimental developments for these pathways as quantified by modeled minimum fuel selling prices (MFSPs), as a measure of current status relative to those final targets. For this SOT, TEA models were run for two separate biological conversion pathways to fuels, based on available data for integrated biomass deconstruction and hydrolysate processing; namely carboxylic acids (primarily butyric acid) and diols (2,3-butanediol [BDO]), reflecting NREL's recently published 2018 biochemical design report focused on those two pathways. The models were run across two scenarios for lignin utilization, namely combustion and conversion to value-added coproducts.

09 BIOMASS FUELS↗

DOE OSTI2025

Bridging the Gap for Powering Data Centers

The rapid expansion of data centers, primarily driven by artificial intelligence, is outpacing the adaptability of the U.S. electric grid. This report, developed by Idaho National Laboratory (INL) , presents a gap analysis of some of the infrastructure challenges associated with large-scale data center deployment. Drawing from a national workshop hosted by INL in October of 2025, the report synthesizes stakeholder insights, survey data, and technical discussions to identify critical barriers and research needs. Key findings highlight the growing preference for behind-the-meter generation, the perceived inadequacy of legacy interconnection processes, and the urgent need for improved coordination between utilities, regulators, and data center developers. Environmental concerns such as water use and noise pollution, as well as economic constraints like equipment lead times and cost allocation, are also explored. The report outlines national lab capabilities in modeling, simulation, and technical assistance, and proposes targeted R&D priorities to support resilient, scalable, and efficient integration of data centers into the grid.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1979

Economic baselines for current underground coal mining technology

The cost of mining coal using a room pillar mining method with continuous miner and a longwall mining system was calculated. Costs were calculated for the years 1975 and 2000 time periods and are to be used as economic standards against which advanced mining concepts and systems will be compared. Some assumptions were changed and some internal model stored data was altered from the original calculations procedure chosen, to obtain a result that more closely represented what was considered to be a standard mine. Coal seam thicknesses were varied from one and one-half feet to eight feet to obtain the cost of mining coal over a wide range. Geologic conditions were selected that had a minimum impact on the mining productivity.

Mabe, W. B.↗

NASA NTRS1986

Concerning the electrosynthesis of hydrogen peroxide and peroxodisulfates. Section 2: Optimization of electrolysis cells using an electrolyzer for peroxodisulfuric acid as an example

The model is presented of an electrolyzer for peroxodisulfuric acid, and it is analyzed mathematically. Its application for engineering and economic optimization is investigated in detail. The mathematical analysis leads to conclusions concerning the change in position of the optimum with respect to the various target functions due to changes of the individual design-caused and economic parameters.

Schleiff, M.↗

NASA NTRS1992

Utilization of space resources in the space transportation system

Utilization of space resources (i.e., raw materials obtained from nonterrestrial sources) has often been cited as a prerequisite for large-scale industrialization and habitation of space. While transportation of extremely large quantities of material from Earth would be costly and potentially destructive to our environment, vast quantities of usable resources might be derived from the Moon, the asteroids, and other celestial objects in a cost-effective and environmentally benign manner. The primary purpose of the parametric cost model developed as part of this study is to identify the factors that have the greatest influence on the economics of space resource utilization. In the near term, this information can be used to devise strategies for technology development so that capabilities developed will produce cost-effective results.

Simon, Michael C.↗

NASA NTRS1997

Estimating the Effects of the Terminal Area Productivity Program

The report describes methods and results of an analysis of the technical and economic benefits of the systems to be developed in the NASA Terminal Area Productivity (TAP) program. A runway capacity model using parameters that reflect the potential impact of the TAP technologies is described. The runway capacity model feeds airport specific models which are also described. The capacity estimates are used with a queuing model to calculate aircraft delays, and TAP benefits are determined by calculating the savings due to reduced delays. The report includes benefit estimates for Boston Logan and Detroit Wayne County airports. An appendix includes a description and listing of the runway capacity model.

Lee, David A.↗

NASA NTRS2009

Complexity for Survival of Living Systems

A logical connection between the survivability of living systems and the complexity of their behavior (equivalently, mental complexity) has been established. This connection is an important intermediate result of continuing research on mathematical models that could constitute a unified representation of the evolution of both living and non-living systems. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the two most relevant being Characteristics of Dynamics of Intelligent Systems (NPO- 21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; and Self-Supervised Dynamical Systems (NPO- 30634) NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72. As used here, living systems is synonymous with active systems and intelligent systems. The quoted terms can signify artificial agents (e.g., suitably programmed computers) or natural biological systems ranging from single-cell organisms at one extreme to the whole of human society at the other extreme. One of the requirements that must be satisfied in mathematical modeling of living systems is reconciliation of evolution of life with the second law of thermodynamics. In the approach followed in this research, this reconciliation is effected by means of a model, inspired partly by quantum mechanics, in which the quantum potential is replaced with an information potential. The model captures the most fundamental property of life - the ability to evolve from disorder to order without any external interference. The model incorporates the equations of classical dynamics, including Newton s equations of motion and equations for random components caused by uncertainties in initial conditions and by Langevin forces. The equations of classical dynamics are coupled with corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces that are gradients of the information potential, which, in turn, is a function of the probability densities. The probability densities are associated with mental images both self-image and nonself images (images of external objects that can include other agents). The evolution of the probability densities represents mental dynamics. Then the interaction between the physical and metal aspects of behavior is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. The interaction of a system with its self and nonself images affords unlimited capacity for increase of complexity. There is a biological basis for this model of mental dynamics in the discovery of mirror neurons that learn by imitation. The levels of complexity attained by use of this model match those observed in living systems. To establish a mechanism for increasing the complexity of dynamics of an active system, the model enables exploitation of a chain of reflections exemplified by questions of the form, "What do you think that I think that you think...?" Mathematically, each level of reflection is represented in the form of an attractor performing the corresponding level of abstraction with more details removed from higher levels. The model can be used to describe the behaviors, not only of biological systems, but also of ecological, social, and economics ones.

Zak, Michail↗

DOE OSTI2023

Bioeconomy Scenario Analysis

The Bioeconomy Scenario Analysis (BSA) project uses systems thinking and analysis to assess how techno economics, research and development, deployment strategies, policy, and market conditions affect the potential development trajectories of the developing bioenergy industry. This project informs researchers, decision makers, and industry by identifying opportunities for and constraints to industrial development and quantifying important industry metrics (e.g., energy, economic, environmental) towards a sustainable domestic bioenergy system. One of the tools used in this project, the Bioenergy Scenario Model (BSM) is a publicly-available, unique, validated, state-of-the-art, award-winning, fourth-generation model of the domestic biofuels supply chain which explicitly focuses on how and under what conditions biofuel technologies might be deployed to contribute to the U.S. transportation energy sector. Analysis products from this effort enable the development of the bioenergy industry by (1) encouraging policy-makers to explore multiple levers simulating outside impacts on biofuels production, identifying policy actions; (2) improving industry's understanding of growth potential under different market conditions, better targeting their development efforts; and (3) providing universities and other interested stakeholders with analysis tools and analyses that can be adapted to meet research and teaching objectives, thus connecting students with careers that build the industry.

bioenergy↗

NASA NTRS2002

Propulsion System Modeling and Simulation

The Aerospace Systems Design Laboratory at the School of Aerospace Engineering in Georgia Institute of Technology has developed a core competency that enables propulsion technology managers to make technology investment decisions substantiated by propulsion and airframe technology system studies. This method assists the designer/manager in selecting appropriate technology concepts while accounting for the presence of risk and uncertainty as well as interactions between disciplines. This capability is incorporated into a single design simulation system that is described in this paper. This propulsion system design environment is created with a commercially available software called iSIGHT, which is a generic computational framework, and with analysis programs for engine cycle, engine flowpath, mission, and economic analyses. iSIGHT is used to integrate these analysis tools within a single computer platform and facilitate information transfer amongst the various codes. The resulting modeling and simulation (M&S) environment in conjunction with the response surface method provides the designer/decision-maker an analytical means to examine the entire design space from either a subsystem and/or system perspective. The results of this paper will enable managers to analytically play what-if games to gain insight in to the benefits (and/or degradation) of changing engine cycle design parameters. Furthermore, the propulsion design space will be explored probabilistically to show the feasibility and viability of the propulsion system integrated with a vehicle.

Tai, Jimmy C. M.↗

DOE OSTI2021

HybridBOSSE (Hybrid Balance-of-System (BOS) Systems Engineering Model)

Hybrid Power Plants (HPPs) have the potential to increase the value of renewable energy systems and decrease their costs through shared development (e.g., permitting) and infrastructure (e.g., collection system). Prior work has identified potential cost savings and technical and economic performance improvements for solar plus storage plants. However, additional research is needed to understand cost drivers that are specific to hybrid wind plants. Here we analyze the potential for shared infrastructure cost savings at one type of hybrid plant: wind plus solar photovoltaic (PV). To perform this analysis, we developed a new open-source, Python-based cost modeling tool: the Hybrid Balance-of-System (BOS) Systems Engineering model (HybridBOSSE). HybridBOSSE is an extension of NREL's LandBOSSE tool.

Barker, Aaron↗

DOE OSTI2023

ABF Past Accomplishments - TEA/LCA

The Integrated Analysis task in the Agile BioFoundry (ABF) conducts techno-economic analysis (TEA) and life cycle assessment (LCA) to quantify the economics and environmental impacts of bioprocesses under development. The team from Argonne National Laboratory (ANL) and the National Renewable Energy Laboratory (NREL) develops TEA and LCA models of selected compound targets and hosts of interest to the ABF in an effort to provide an analysis-based foundation to the R&D. To date, the Integrated Analysis task has performed process modeling and analyses on multiple pairings of bioproducts and hosts, centered around major metabolic "beachheads" and "exemplar" molecules chosen for each of the metabolic pathways of interest. This presentation provides an overview of the approach used for TEA and LCA in the ABF and of the progress, outcomes, and impacts of TEA and LCA to support ABF goals, with a focus towards developing bio-based products that are both environmentally and economically viable.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

NASA NTRS2014

Environmental and Socio-Demographic Determinants of Dengue Fever in Colombo City, Sri Lanka

Dengue fever has increased exponentially in Sri Lanka, from 24.4 cases per 100,000 in 2003 to 165.3 per 100,000 population in 2013. Although early warning systems using predictor models have been previously developed in other settings, it is important to develop such models in each local setting. Further, the ability of these models to be applicable at smaller geographic units will enhance current vector control and disease surveillance measures. The aim of this paper was to identify environmental and socio-economic status (SES) risk factors that may predict dengue fever at the Gram Niladhari Divisions (GND) level (smallest administrative unit) in Colombo city, Sri Lanka. These factors included landcover classes, amount of vegetation, population density, water access and neighborhood SES as determined by roof type. A geographically weighted regression (GWR) was used to develop the prediction model. A total 55 GND units covering an area of 37 sq km were investigated. We found that GND units with decreased vegetation, higher built-up area, higher population density and poor access to tap-water supply were associated with high risk of dengue; the pertinent GND units were concentrated in the center of the city. This is the first study in Sri Lanka to include both environmental and socio-demographic factors in prediction models for dengue fever. The methodology may be useful in enhancing ongoing dengue fever control measures in the country, and to be extended to other countries in the region that have an increasing incidence of dengue fever.

Tipre, Meghan↗

DOE OSTI2020

NREL's Capabilities in Biorefinery Analysis

NREL remains at the forefront of expertise in conducting process, techno-economic, and life cycle analyses to connect research with future commercial process integration, a critical step in the scale-up of biomass conversion technologies. Technology areas covered include lignocellulosic biorefineries, algae, CO2 utilization, waste-to-energy, aviation and marine fuels, refinery modeling and analysis, and the circular economy.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

NASA NTRS1980

A global biogeocenotical biosphere simulation

This model of the D. Forrester type, constructed in differential equations, predicts the food and mineral supply for the factors biosphere population, depending on two socio-economic factors, until about the year 2500. If contemporary rates of natural resources utilization are maintained and there is no management of the environment, food resources will begin to limit human population growth after 2200, and mineral resources will after 2300. A decrease in the biosphere pollution, increase in effective agricultural production, and discovery of new energy sources may forestall or completely avert the onset of a crisis situation. Conservation measures, according to the model, are to a considerable extent realizable only if carried out simultaneously in both areas.

Moiseyev, N. N.↗

DOE OSTI2024

Toward High-Throughput Deposition of III-V Materials and Devices Using Halide Vapor Phase Epitaxy: Preprint

III-V devices are used in countless applications due to their excellent physical properties. They could become more prevalent, especially in area-intensive applications such as solar power, if they can achieve significant cost decreases through increasing scale. The development of high-throughput growth systems can help to achieve this scale, leading to the use of III-V devices in areas where they are not currently economically feasible. Here, we describe a pilot production, pseudo inline HVPE reactor with the potential to greatly increase the throughput of III-V devices. We show computational modeling results that both informed system design and the understanding of the impact of different process parameters on the deposition. We show the throughput possibilities of this reactor with an example solar cell device design but note that this system is agnostic to the device structure and can be used to increase the throughput of lasers, LEDs, transistors, and more III-V devices.

high throughput↗

DOE OSTI2022

Industrial battery operation and utilization in the presence of electrical load uncertainty using Bayesian decision theory

Behind the meter battery storage is becoming increasing popular in all sectors, though enthusiasm has recently lagged in the industrial sector. Even though there may be many factors contributing to this including lack of innovation, prohibitive costs, and undesirable rate structures, a difficulty arises in accounting for uncertainty of electrical load in industrial facilities while still attempting to utilize battery storage as much as possible all while trying to achieve fiscal profitability. Here this study utilizes Gaussian process regression and Bayesian decision theory to organize load data and quantify electrical load uncertainty to properly and effectively discharge industrial battery storage. The study employs a simulation model to set battery load setpoints for the span of the utility billing period according to the degree of risk aversion. This combination of economic analysis according to utility billing period and utilization of degree of risk aversion to make decisions on the uncertainty of the data has not before been applied to battery storage. The method resulted in an annual average reduction of peak demand by 3.8 % at the lowest amount of savings and lowest risk aversion. The highest risk aversion resulted in an annual average reduction of peak demand of 7.5 %. The maximum reduction of peak load in any month was 13.8 % in the month of December with a relatively high risk aversion. With a the highest amount risk aversion tested, the model reduced demand ten of the twelve months of the year.

25 ENERGY STORAGE↗