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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Multibody model reduction by component mode synthesis and component cost analysis

The classical assumed-modes method is widely used in modeling the dynamics of flexible multibody systems. According to the method, the elastic deformation of each component in the system is expanded in a series of spatial and temporal functions known as modes and modal coordinates, respectively. This paper focuses on the selection of component modes used in the assumed-modes expansion. A two-stage component modal reduction method is proposed combining Component Mode Synthesis (CMS) with Component Cost Analysis (CCA). First, each component model is truncated such that the contribution of the high frequency subsystem to the static response is preserved. Second, a new CMS procedure is employed to assemble the system model and CCA is used to further truncate component modes in accordance with their contribution to a quadratic cost function of the system output. The proposed method is demonstrated with a simple example of a flexible two-body system.

Spanos, J. T.↗
NASA NTRS2004

Advanced Technology Lifecycle Analysis System (ATLAS)

Developing credible mass and cost estimates for space exploration and development architectures require multidisciplinary analysis based on physics calculations, and parametric estimates derived from historical systems. Within the National Aeronautics and Space Administration (NASA), concurrent engineering environment (CEE) activities integrate discipline oriented analysis tools through a computer network and accumulate the results of a multidisciplinary analysis team via a centralized database or spreadsheet Each minute of a design and analysis study within a concurrent engineering environment is expensive due the size of the team and supporting equipment The Advanced Technology Lifecycle Analysis System (ATLAS) reduces the cost of architecture analysis by capturing the knowledge of discipline experts into system oriented spreadsheet models. A framework with a user interface presents a library of system models to an architecture analyst. The analyst selects models of launchers, in-space transportation systems, and excursion vehicles, as well as space and surface infrastructure such as propellant depots, habitats, and solar power satellites. After assembling the architecture from the selected models, the analyst can create a campaign comprised of missions spanning several years. The ATLAS controller passes analyst specified parameters to the models and data among the models. An integrator workbook calls a history based parametric analysis cost model to determine the costs. Also, the integrator estimates the flight rates, launched masses, and architecture benefits over the years of the campaign. An accumulator workbook presents the analytical results in a series of bar graphs. In no way does ATLAS compete with a CEE; instead, ATLAS complements a CEE by ensuring that the time of the experts is well spent Using ATLAS, an architecture analyst can perform technology sensitivity analysis, study many scenarios, and see the impact of design decisions. When the analyst is satisfied with the system configurations, technology portfolios, and deployment strategies, he or she can present the concepts to a team, which will conduct a detailed, discipline-oriented analysis within a CEE. An analog to this approach is the music industry where a songwriter creates the lyrics and music before entering a recording studio.

O'Neil, Daniel A.↗
DOE OSTI2020

A nonparametric approach to modeling dependence among production parameters for energy cost estimation

Dependence existing among production parameters can significantly affect energy costs. For material removal processes, processing times and material amounts to be cut have positive dependence, and the dependence can affect energy costs by varying a peak electricity load. Existing methods to model the dependence of production parameters are based on parametric approaches that cannot accurately represent the dependence due to the rigid nature of parametric models. To address this issue, this study proposes a method to quantify dependence among manufacturing parameters through the application of the empirical copula to the dependence between the milling processing time and the amount of volume to be cut. The proposed method is illustrated by a case study of a manufacturing facility consisting of milling machines; a total of 27 scenarios are simulated for energy cost estimations. The case study clearly shows that the proposed method can capture the dependence between the milling parameters more accurately than a conventional dependence measure from parametric correlation models. Furthermore, the findings from this study would be useful to estimate energy costs in that the proposed method provides a better fit to real production data than conventional parametric approaches can.

42 ENGINEERING↗
NASA NTRS2002

Software for Estimating Costs of Testing Rocket Engines

A high-level parametric mathematical model for estimating the costs of testing rocket engines and components at Stennis Space Center has been implemented as a Microsoft Excel program that generates multiple spreadsheets. The model and the program are both denoted, simply, the Cost Estimating Model (CEM). The inputs to the CEM are the parameters that describe particular tests, including test types (component or engine test), numbers and duration of tests, thrust levels, and other parameters. The CEM estimates anticipated total project costs for a specific test. Estimates are broken down into testing categories based on a work-breakdown structure and a cost-element structure. A notable historical assumption incorporated into the CEM is that total labor times depend mainly on thrust levels. As a result of a recent modification of the CEM to increase the accuracy of predicted labor times, the dependence of labor time on thrust level is now embodied in third- and fourth-order polynomials.

Hines, Merion M.↗
NASA NTRS2004

Software for Estimating Costs of Testing Rocket Engines

A high-level parametric mathematical model for estimating the costs of testing rocket engines and components at Stennis Space Center has been implemented as a Microsoft Excel program that generates multiple spreadsheets. The model and the program are both denoted, simply, the Cost Estimating Model (CEM). The inputs to the CEM are the parameters that describe particular tests, including test types (component or engine test), numbers and duration of tests, thrust levels, and other parameters. The CEM estimates anticipated total project costs for a specific test. Estimates are broken down into testing categories based on a work-breakdown structure and a cost-element structure. A notable historical assumption incorporated into the CEM is that total labor times depend mainly on thrust levels. As a result of a recent modification of the CEM to increase the accuracy of predicted labor times, the dependence of labor time on thrust level is now embodied in third- and fourth-order polynomials.

Hines, Merlon M.↗
NASA NTRS2003

Software for Estimating Costs of Testing Rocket Engines

A high-level parametric mathematical model for estimating the costs of testing rocket engines and components at Stennis Space Center has been implemented as a Microsoft Excel program that generates multiple spreadsheets. The model and the program are both denoted, simply, the Cost Estimating Model (CEM). The inputs to the CEM are the parameters that describe particular tests, including test types (component or engine test), numbers and duration of tests, thrust levels, and other parameters. The CEM estimates anticipated total project costs for a specific test. Estimates are broken down into testing categories based on a work-breakdown structure and a cost-element structure. A notable historical assumption incorporated into the CEM is that total labor times depend mainly on thrust levels. As a result of a recent modification of the CEM to increase the accuracy of predicted labor times, the dependence of labor time on thrust level is now embodied in third- and fourth-order polynomials.

Hines, Merlon M.↗
DOE OSTI2021

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks: Q1 2021

Based on our bottom-up modeling, the Q1 2021 PV and energy storage cost benchmarks are: $\$2.65$ per watt DC (WDC) (or $\$3.05$/WAC) for residential PV systems, 1.56/WDC (or $\$1.79$/WAC) for commercial rooftop PV systems, $\$1.64$/WDC (or $\$1.88$/WAC) for commercial ground-mount PV systems, $\$0.83$/WDC (or $\$1.13$/WAC) for fixed-tilt utility-scale PV systems, $\$0.89$/WDC (or $\$1.20$/WAC) for one-axis-tracking utility-scale PV systems, $\$30,326$-$\$33,618$ for a 7.15-kWDC residential PV system with 5 kW/12.5 kWh nameplate of storage, $\$2.04$ - $\$2.10$ million for a 1-MWDC commercial ground-mount PV system colocated with 600 kW/2.4 MWhusable of storage, $\$166$ - $\$167$ million for a 100-MWDC one-axis tracker PV system colocated with 60 MW/240 MWhusable of storage. Between 2020 and 2021, there were 3.3% ($\$0.0$9/W), 10.7% ($\$0.19$/W), and 12.3% ($\$0.13$/W) reductions (in 2020 USD) in the residential, commercial rooftop, and utility-scale (one-axis) PV system cost benchmarks respectively. Balance of system (BOS) costs have either increased or remained flat across sectors, year-on-year, unlike in previous benchmark reports, which generally have reported declining BOS costs. The increase in BOS cost has been offset by a 17% reduction in module cost. Overall, modeled PV installed costs across the three sectors have declined compared to our Q1 2020 system costs.

14 SOLAR ENERGY↗
DOE OSTI2023

Benchmarking Microscale Ductility Measurements (Final Report of the Project DE-NE0008799)

Conventional macroscale experimentation is generally considered to be straightforward with few limitations. Conversely, micro/nanoscale experimentation presents numerous challenges in loading device design, sample preparation and handling, as well as accurate understanding of grain size and local texture effects on recorded measurements. Despite these challenges, nanopillar compression, MEMs based micro-tension, and nanoindentation approaches have been able to provide fundamental contributions to the understanding of material behavior at small lengthscales. However, the overarching shortcoming of these micro/nanoscale experimentation approaches, is the inability to directly translate measurements evaluated at the nm and µm length scales (e.g., hardness) to macroscale tensile material behavior (i.e., elastic modulus, yield strength, and ductility). The objectives of the proposed study are, 1) to establish best practices for obtaining tensile microscale ductility measurements, and 2) to validate methodologies to for comparing microscale ductility measurements to macroscale ductility measurements. In order to achieve these objectives, a multi-lengthscale, multi-temperature testing protocol and simulation framework are executed first on copper as a model material to validate the following approach, and second on reactor grade Zircaloy-2. Experiments are conducted on specimens extracted from the same test piece to ensure nominally identical grain size and texture from specimens to specimen. Motivated by the need to isolate the contribution of size-effects on obtained mechanical property measurements, specimens are manufactured with thicknesses at the micro- (1-10 µm), meso- (10-100's µm), and macroscales (sub-sized ASTM E8). In-situ full-field deformation techniques (scanning electron microscopy (SEM) grid methods and optical DIC) are incorporated into testing at each specimen length-scale to capture plasticity localization and evolution. Experimental testing for all specimens is conducted at both room temperature and elevated temperatures to probe the role of thermal activation on plastic deformation accommodation processes. Simulation efforts focus on examining the mechanical behavior of microscale specimens using a finite element approach with explicitly resolved grain morphologies, and an embedded crystal plasticity model. The cost-efficient implementation method allows for the modeling of a statistically significant number of both real (i.e., digital twin) and generated microstructures to obtain an understanding of the interrelationships between specimen microstructure and geometric variables (grain size, texture, specimen geometry, etc.) on microscale mechanical behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A permafrost implementation in the simple carbon–climate model Hector v.2.3pf

Abstract. Permafrost currently stores more than a fourth of global soil carbon. A warming climate makes this carbon increasingly vulnerable to decomposition and release into the atmosphere in the form of greenhouse gases. The resulting climate feedback can be estimated using land surface models, but the high complexity and computational cost of these models make it challenging to use them for estimating uncertainty, exploring novel scenarios, and coupling with other models. We have added a representation of permafrost to the simple, open-source global carbon–climate model Hector, calibrated to be consistent with both historical data and 21st century Earth system model projections of permafrost thaw. We include permafrost as a separate land carbon pool that becomes available for decomposition into both methane (CH4) and carbon dioxide (CO2) once thawed; the thaw rate is controlled by region-specific air temperature increases from a preindustrial baseline. We found that by 2100 thawed permafrost carbon emissions increased Hector’s atmospheric CO2 concentration by 5 %–7 % and the atmospheric CH4 concentration by 7 %–12 %, depending on the future scenario, resulting in 0.2–0.25 ∘C of additional warming over the 21st century. The fraction of thawed permafrost carbon available for decomposition was the most significant parameter controlling the end-of-century temperature change in the model, explaining around 70 % of the temperature variance, and was distantly followed by the initial stock of permafrost carbon, which contributed to about 10 % of the temperature variance. The addition of permafrost in Hector provides a basis for the exploration of a suite of science questions, as Hector can be cheaply run over a wide range of parameter values to explore uncertainty and can be easily coupled with integrated assessment and other human system models to explore the economic consequences of warming from this feedback.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

The steady-state flow quality of an open return wind tunnel model.

The structural cost of open return wind tunnels is significantly less than that of the more conventional closed return wind tunnels. However, because of the effects of external winds, the flow quality of open return wind tunnels is an area of concern at the low speeds required for V/STOL testing. The development of a configuration which has good flow quality at low as well as at high test speeds is described. The flow quality required at the low test speeds of interest for V/STOL aircraft is discussed and alternatives to the traditional manner of specifying the flow quality requirements in terms of dynamic pressure and angle of attack are suggested.

Mort, K. W.↗
NASA NTRS2021

A permafrost implementation in the simple carbon-climate model Hector v.2.3.pf

Permafrost currently stores more than a fourth of global soil carbon. A warming climate makes this carbon increasingly vulnerable to decomposition and release into the atmosphere in the form of greenhouse gases. The resulting climate feedback can be estimated using land surface models, but the high complexity and computational cost of these models make it challenging to use them for estimating uncertainty, exploring novel scenarios, and coupling with other models. We have added a representation of permafrost to the simple, open-source global carbon–climate model Hector, calibrated to be consistent with both historical data and 21st century Earth system model projections of permafrost thaw. We include permafrost as a separate land carbon pool that becomes available for decomposition into both methane (CH4) and carbon dioxide (CO2) once thawed; the thaw rate is controlled by region-specific air temperature increases from a preindustrial baseline. We found that by 2100 thawed permafrost carbon emissions increased Hector’s atmospheric CO2 concentration by 5 %–7 % and the atmospheric CH4 concentration by 7 %–12 %, depending on the future scenario, resulting in 0.2–0.25 ∘C of additional warming over the 21st century. The fraction of thawed permafrost carbon available for decomposition was the most significant parameter controlling the end-of-century temperature change in the model, explaining around 70 % of the temperature variance, and was distantly followed by the initial stock of permafrost carbon, which contributed to about 10 % of the temperature variance. The addition of permafrost in Hector provides a basis for the exploration of a suite of science questions, as Hector can be cheaply run over a wide range of parameter values to explore uncertainty and can be easily coupled with integrated assessment and other human system models to explore the economic consequences of warming from this feedback.

Dawn L. Woodard↗
DOE OSTI2020

Estimation of abatement potentials and costs of air pollution emissions in China

Understanding the air pollution emission abatement potential and associated control cost is a prerequisite to design cost ef?cient control policies. In this study, a linear programming algorithm model, International Control Cost Estimate Tool, was updated with cost data for applications of 56 types of end-of-pipe technologies and ?ve types of renewable energy in 10 major sectors namely power generation, industry combustion, cement pro-duction, iron and steel production, other industry processes, domestic combustion, transportation, solvent use, livestock rearing, and fertilizer use. The updated model was implemented to estimate the abatement potential and marginal cost of multiple pollutants in China. The total maximum abatement potentials of sulfur dioxide (SO2), nitrogen oxides (NOx), primary particulate matter (PM2.5), non-volatile organic compounds (NMVOCs), and ammonia (NH3) in China were estimated to be 19.2, 20.8, 9.1, 17.2 and 8.6 Mt, respectively, which accounted for 89.7%, 89.9%, 94.6%, 74.0%, and 80.2% of their total emissions in 2014, respectively. The associated control cost of such reductions was estimated as 92.5, 469.7, 75.7, 449.0, and 361.8 billion CNY in SO2, NOx, primary PM2.5, NMVOCs and NH3, respectively. Shandong, Jiangsu, Henan, Zhejiang, and Guangdong provinces exhibited large abatement potentials for all pollutants. Provincial disparity analysis shows that high GDP regions tend to have higher reduction potential and total abatement costs. End-of-pipe technologies tended be a cost-ef?cient way to control pollution in industries processes (i.e., cement plants, iron and steel plants, lime production, building ceramic production, glass and brick production), whereas such technologies were less cost- effective in fossil fuel-related sectors (i.e., power plants, industry combustion, domestic combustion, and transportation) compared with renewable energy. The abatement potentials and marginal abatement cost curves developed in this study can further be used as a crucial component in an integrated model to design optimized cost-ef?cient control policies.

Zhang, Fenfen↗
DOE OSTI2022

Evaluating the Impact of Residential Solar Contract Cancellations in the United States

The residential solar photovoltaic (PV) market in the United States is growing, despite frequent customer cancellations. Contract cancellations result in lost time and costs that must be borne by installers, often in the form of higher "soft costs" (i.e., non-equipment costs). These costs are often passed on to customers who successfully install PV systems. To date, few studies have attempted to estimate national cancellation rates or model the impacts on installed system costs. In this report, we utilize an installer-provided dataset of 199,665 residential PV-only projects representing about 10% of U.S. installs each year from 2017-2019. With this data, we evaluate cancellation rates and trends from contract signing to install. Next, by leveraging NREL's soft cost model for residential solar, we estimate installer spending through each phase of the pre-install process. Applying our findings on cancellation timelines and rates, we then estimate the potential cost impacts to successful installs from contract cancellations. Our work suggests that the rates and impacts of contract cancellations have been previously underestimated. Namely, we find that cancellations/unsuccessful project are; more common than previous estimates suggest; occur earlier in project timelines, though a significant number happen even after permit/ATB approvals; and contribute significantly to customer acquisition and other soft costs. We also find that cancellation do not appear to be driven by review delays in permitting and interconnection applications.

14 SOLAR ENERGY↗
DOE OSTI2024

Accelerated CO2 Storage Optimization Using Multi-Resolution Fourier Neural Operator at the Illinois Basin Decatur Project (IBDP)

This paper presents a deep learning-based approach for optimizing CO2 injection in carbon capture and storage (CCS) operations. We developed a multi-resolution machine learning model to significantly reduce data generation costs. Utilizing this proxy model, we implemented a multi-objective genetic algorithm to optimize well control during the CO2 injection process. The proposed approach was applied to the Illinois Basin Decatur Project (IBDP), successfully optimizing the CO2 injection schedule based on three key objectives: maximizing the amount of CO2 stored, maximizing sweep efficiency, and minimizing pressure increase. The use of the proxy model accelerated the optimization workflow by two orders of magnitude, while the cost of data generation for the proxy model was reduced by 90% by utilizing a coarse-scale model.

accelerated CO2 storage optimization↗
NASA NTRS1980

Cost decomposition of linear systems with application to model reduction

A means is provided to assess the value or 'cst' of each component of a large scale system, when the total cost is a quadratic function. Such a 'cost decomposition' of the system has several important uses. When the components represent physical subsystems which can fail, the 'component cost' is useful in failure mode analysis. When the components represent mathematical equations which may be truncated, the 'component cost' becomes a criterion for model truncation. In this latter event component costs provide a mechanism by which the specific control objectives dictate which components should be retained in the model reduction process. This information can be valuable in model reduction and decentralized control problems.

Skelton, R. E.↗
DOE OSTI2022

Building Energy Modeling Enhancements to Identify Least-Cost Pathways to Net-Zero Carbon Homes: Preprint

Residential grid-interactive efficient buildings (GEBs) can utilize high levels of energy efficiency and demand flexibility to deliver value to occupants, the grid, and society. However, without the ability to analyze, design, and optimize residential GEBs there is a risk that homes will not realize their full potential value as efficient and dynamic resources, which could ultimately lead to higher than necessary energy costs for U.S. households and lower realization of potential energy efficiency and demand flexibility benefits such as increased convenience/automation, thermal comfort, durability, indoor air quality, and resilience. In 2018, the National Renewable Energy Laboratory (NREL) Residential Modeling Team developed a vision for an open source Residential GEB Analytics Platform built within DOE's EnergyPlus and OpenStudio modeling environment that would enable the design and optimization of residential GEBs, including the identification of least-cost pathways to highly energy-efficient and energy-flexible homes (e.g., net zero carbon homes). We created a detailed workplan for the development of new and enhanced residential GEB component-level models for EnergyPlus and OpenStudio needed to progress toward the vision for the analytics platform while delivering near-term benefits to industry. This paper 1) presents the vision for the platform, summarizing the workplan for residential GEB modeling enhancements; 2) highlights significant advancements that have been achieved between 2018 and 2022, including stochastic residential occupancy modeling, flexible water heater modeling, detailed lithium-ion stationary battery modeling, and realistic residential HVAC modeling; and 3) outlines ongoing efforts and next steps toward the full vision for the platform.

building energy modeling↗