Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cost 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.

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

At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Collisional stopping power of ions in warm dense matter

Here, a model for the collisional stopping of ions on free electrons in warm dense matter is developed and explored. It is based on plasma kinetic theory, but with modifications to address the warm dense matter regime. Specifically, it uses the Boltzmann-Uehling-Uhlenbeck kinetic equation to incorporate effects of Fermi degeneracy of electrons. The cross section is computed from quantum scattering of electrons and ions occurring via the potential of mean force derived from an average atom model, which incorporates effects of strong Coulomb correlations. Predictions from this model show comparable accuracy to results from time-dependent density functional theory calculations for deuterium near solid density and a temperature of several electronvolts, at a fraction of the computational cost. Further, the model captures the transition of a plasma from the classical limit to the degenerate limit, including qualitative behaviors of solid state theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Advances in Modeling Capabilities for Critical Mineral Separation Technologies: A PrOMMiS Overview

This is an oral presentation at the TechConnect conference on the work developed by PrOMMiS. PrOMMiS builds on and extends capabilities developed within the Department of Energy’s (DOE) Institute for the Design of Advanced Energy Systems (IDAES), Integrated Platform, and Water Treatment Technoeconomic Assessment Platform (WaterTAP), which have been successfully leveraged by other Department of Energy research areas. The open-source toolkit facilitates validation, reproducibility, and accountability, allowing for easy extension of the framework to other systems. This talk presents an overview of the PrOMMiS capabilities, including unit model library, advances in thermophysical properties models, and capital cost libraries for simulation and optimization of mineral processing technologies. The PrOMMiS applications include (1) conceptual design and superstructure optimization for screening different process configurations and identifying promising technologies; (2) dynamic modeling and optimization to enable the creation of digital twins; (3) surrogate modeling tools to leverage data when predictive thermodynamic models are not currently available; (4) technical risk reduction via uncertainty quantification and robust optimization to identify process designs that are robust to process variability and uncertainties; and (5) deployment of uncertainty quantification tools to maximize knowledge gained from experimental campaigns, while reducing the number of experiments required

critical minerals and materials↗
NASA NTRS1998

Aerodynamic Properties Analysis of Rapid Prototyped Models Versus Conventional Machined Models

Initial studies of the aerodynamic characteristics of proposed launch vehicles can be made more accurately if lower cost, high fidelity aerodynamic models are available for wind tunnel testing early in the design phase. This paper discusses the results of a study undertaken at NASA's Marshall Space Flight Center to determine if four rapid prototyping methods using a variety of materials are suitable for the design and manufacturing of high speed wind tunnel models in direct testing applications. It also gives an analysis of whether these materials and processes are of sufficient strength and fidelity to withstand the testing environment. In addition to test data, costs and turn-around times for the various models are given. Based on the results of this study, it can be concluded that rapid prototyping models show promise in limited direct application for preliminary aerodynamic development studies at subsonic, transonic, and supersonic speeds.

Springer, A.↗
DOE OSTI2026

A PRACTICAL ELECTRODIALYSIS MODEL FOR ACCELERATING SYSTEM DEVELOPMENT

Empirical optimization of electrodialysis (ED) is dependent on repetitive experiments with incremental adjustments, which is cost prohibitive at scale. While models can reduce the costs associated with optimization and scale-up, existing ED models are limited in application to specific use cases and tend to be developed for the exploration of specific transport phenomena. The field requires a practical system-level model, generalized for the broad range of ED systems. This work presents a modeling framework that enables rapid evaluation of membrane stack design, flow configuration, scale, and operational inputs. Across applications spanning 1 L to 5400 L; use of conventional and bipolar membranes; operation in continuous, batch and fed-batch modes; and feedstocks including seawater, brine, wastewater, and manure hydrolysate, the model achieves a mean R2 of 0.978 for concentration-time profiles and links design choices to techno-economic trade-offs, enabling cost-aware prioritization of system configurations.

Bipolar Membrane↗
NASA NTRS2007

Shell Models of RMHD Turbulence and the Heating of Solar Coronal Loops

A simplified nonlinear numerical model for the development of incompressible magnetohydrodynamics in the presence of a strong magnetic field B|| and stratification, nicknamed 'Shell-Atm,' is presented. In planes orthogonal to the mean field, the nonlinear incompressible dynamics is replaced by two-dimensional shell models for the complex variables u and b, allowing one to reach large Reynolds numbers while at the same time carrying out sufficiently long integrations to obtain good statistics at moderate computational cost. The shell models of different planes are coupled by Alfve'n waves propagating along B||. The model may be applied to open or closed magnetic field configurations where the axial field dominates and the plasma pressure is low; here we apply it to the specific case of a magnetic loop of the solar corona heated by means of turbulence driven by photospheric motions, and we use statistics for its analysis. The Alfven waves interact nonlinearly and form turbulent spectra in the directions perpendicular and, through propagation, also parallel to the mean field. A heating function is obtained and shown to be intermittent; the average heating is consistent with values required for sustaining a hot corona and is proportional to the aspect ratio of the loop to the -1.5 power, and haracteristic properties of heating events are distributed as power laws. Crosscorrelations show a delay of dissipation compared with energy content.

corona↗
NASA NTRS2013

Maintaining Adequate Carbon Dioxide Washout for an Advanced Extravehicular Mobility Unit

Over the past several years, NASA has realized tremendous progress in technology development that is aimed at the production of an Advanced Extravehicular Mobility Unit (AEMU). Of the many functions provided by the spacesuit and portable life support subsystem within the AEMU, delivering breathing gas to the astronaut along with removing the carbon dioxide (CO2) remains one of the most important environmental functions that the AEMU can control. Carbon dioxide washout is the capability of the ventilation flow in the spacesuit helmet to provide low concentrations of CO2 to the crew member to meet breathing requirements. CO2 washout performance is a critical parameter needed to ensure proper and sufficient designs in a spacesuit and in vehicle applications such as sleep stations and hygiene compartments. Human testing to fully evaluate and validate CO2 washout performance is necessary but also expensive due to the levied safety requirements. Moreover, correlation of math models becomes challenging because of human variability and movement. To supplement human CO2 washout testing, a breathing capability will be integrated into a suited manikin test apparatus to provide a safe, lower cost, stable, easily modeled alternative to human testing. Additionally, this configuration provides NASA Johnson Space Center (JSC) the capability to evaluate CO2 washout under off-nominal conditions that would otherwise be unsafe for human testing or difficult due to fatigue of a test subject. Testing has been under way in-house at JSC and analysis has been initiated to evaluate whether the technology provides sufficient performance in ensuring that the CO2 is removed sufficiently and the ventilation flow is adequate for maintaining CO2 washout in the AEMU spacesuit helmet of the crew member during an extravehicular activity. This paper will review recent CO2 washout testing and analysis activities, testing planned in-house with a spacesuit simulator, and the associated analytical work along with insights from the medical aspect on the testing.

Chullen, Cinda↗
NASA NTRS1990

Analysis of success probability/cost trades for small landers in a Mars network

The premise to be tested in this analysis is whether cost economics may accrue by delivering more landers designed to lower reliability of operation (compared to fewer landers of higher reliability) to obtain a desired probability of achieving a given number of lander successes. Generally, the application in mind is a network of penetrators, although the analysis may apply as well to other small lander concepts or even to simple rovers. The method of analysis is based on a probabilistic model of lander success and a related probabilistic model of project cost including the lander, spacecraft carrier, and integration, but not launch or operations costs. Quantitative results are obtained in a normalized and parametric fashion. Sensitivity to the assumed model parameters is also examined.

Friedlander, Alan L.↗
DOE OSTI2022

Global biomass supply modeling for long-run management of the climate system

Bioenergy is projected to have a prominent, valuable, and maybe essential, role in climate management. However, there is significant variation in projected bioenergy deployment results, as well as concerns about the potential environmental and social implications of supplying biomass. Bioenergy deployment projections are market equilibrium solutions from integrated modeling, yet little is known about the underlying modeling of the supply of biomass as a feedstock for energy use in these modeling frameworks. We undertake a novel diagnostic analysis with ten global models to elucidate, compare, and assess how biomass is supplied within the models used to inform long-run climate management. With experiments that isolate and reveal biomass supply modeling behavior and characteristics (costs, emissions, land use, market effects), we learn about biomass supply tendencies and differences. The insights provide a new level of modeling transparency and understanding of estimated global biomass supplies that informs evaluation of the potential for bioenergy in managing the climate and interpretation of integrated modeling. For each model, we characterize the potential distributions of global biomass supply across regions and feedstock types for increasing levels of quantity supplied, as well as some of the potential societal externalities of supplying biomass. We also evaluate the biomass supply implications of managing these externalities. Finally, we interpret biomass market results from integrated modeling in terms of our new understanding of biomass supply. Overall, we find little consensus between models on where biomass could be cost-effectively produced and the implications. We also reveal model specific biomass supply narratives, with results providing new insights into integrated modeling bioenergy outcomes and differences. The analysis finds that many integrated models are considering and managing emissions and land use externalities of supplying biomass and estimating that environmental and societal trade-offs in the form of land emissions, land conversion, and higher agricultural prices are cost-effective, and to some degree a reality of using biomass, to address climate change.

09 BIOMASS FUELS↗
DOE OSTI2022

Updated Economic Model for Estimation of GDP Losses in the MACCS Offsite Consequence Analysis Code RDEIM Model Report for MACCS v4.2

This report updates the Regional Disruption Economic Impact Model (RDEIM) GDP-based model described in Bixler et al. (2020) used in the MACCS accident consequence analysis code. MACCS is the U.S. Nuclear Regulatory Commission (NRC) used to perform probabilistic health and economic consequence assessments for atmospheric releases of radionuclides. It is also used by international organizations, both reactor owners and regulators. It is intended and most commonly used for hypothetical accidents that could potentially occur in the future rather than to evaluate past accidents or to provide emergency response during an ongoing accident. It is designed to support probabilistic risk and consequence analyses and is used by the NRC, U.S. nuclear licensees, the Department of Energy, and international vendors, licensees, and regulators. The update of the RDEIM model in version 4.2 expresses the national recovery calculation explicitly, rather than implicitly as in the previous version. The calculation of the total national GDP losses remains unchanged. However, anticipated gains from recovery are now allocated across all the GDP loss types – direct, indirect, and induced – whereas in version 4.1, all recovery gains were accounted for in the indirect loss type. To achieve this, we’ve introduced new methodology to streamline and simplify the calculation of all types of losses and recovery. In addition, RDEIM includes other kinds of losses, including tangible wealth. This includes loss of tangible assets (e.g., depreciation) and accident expenditures (e.g., decontamination). This document describes the updated RDEIM economic model and provides examples of loss and recovery calculation, results analysis, and presentation. Changes to the tangible cost calculation and accident expenditures are described in section 2.2. The updates to the RDEIM input-output (I-O) model are not expected to affect the final benchmark results Bixler et al. (2020), as the RDEIM calculation for the total national GDP losses remains unchanged. The reader is referred to the MACCS revision history for other cost modelling changes since version 4.0 that may affect the benchmark. RDEIM has its roots in a code developed by Sandia National Laboratories for the Department of Homeland Security to estimate short-term losses from natural and manmade accidents, called the Regional Economic Accounting analysis tool (REAcct). This model was adapted and modified for MACCS. It is based on I-O theory, which is widely used in economic modeling. It accounts for direct losses to a disrupted region affected by an accident, indirect losses to the national economy due to disruption of the supply chain, and induced losses from reduced spending by displaced workers. RDEIM differs from REAcct in in its treatment and estimation of indirect loss multipliers, elimination of double-counting associated with inter-industry trade in the affected area, and that it is intended to be used for extended periods that can occur from a major nuclear reactor accident, such as the one that occurred at the Fukushima Daiichi site in Japan. Most input-output models do not account for economic adaptation and recovery, and in this regard RDEIM differs from its parent, REAcct, because it allows for a user-definable national recovery period. Implementation of a recovery period was one of several recommendations made by an independent peer review panel to ensure that RDEIM is state-of-practice. For this and several other reasons, RDEIM differs from REAcct.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Calomplification — the power of generative calorimeter models

Motivated by the high computational costs of classical simulations, machine-learned generative models can be extremely useful in particle physics and elsewhere. They become especially attractive when surrogate models can efficiently learn the underlying distribution, such that a generated sample outperforms a training sample of limited size. This kind of GANplification has been observed for simple Gaussian models. We show the same effect for a physics simulation, specifically photon showers in an electromagnetic calorimeter.

47 OTHER INSTRUMENTATION↗
NASA NTRS2001

A Geosynchronous Lidar System for Atmospheric Winds and Moisture Measurements

An observing system comprised of two lidars in geosynchronous orbit would enable the synoptic and meso-scale measurement of atmospheric winds and moisture, both of which are key first-order variables of the Earth's weather equation. Simultaneous measurement of these parameters at fast revisit rates promises large advancements in our weather prediction skills. Such capabilities would be unprecedented and yield greatly improved and finer resolution initial conditions for models, make existing costly and cumbersome measurement approaches obsolete, and obviate the use of numerical techniques needed to correct data obtained using present observing systems. Additionally, simultaneous synoptic wind and moisture observations would lead to improvements in model parameterizations, and in our knowledge of small-scale weather processes. Technology and science data product assessments are ongoing. Results will be presented during the conference.

Emmitt, G. D.↗
DOE OSTI2025

Comparison of interlaminar damage modeling strategies for hybrid composite/aluminum laminates subjected to low-velocity impact

Low-velocity impact of hybrid metal-composite structures was investigated experimentally and computationally. Composite laminates consisting of 2D woven glass fiber reinforced polymer (GFRP) and carbon fiber reinforced polymer (CFRP) were joined with a 6061-T6 aluminum plate using an epoxy adhesive. Two variations of the structure were studied; one consisting of all plies oriented at 0° and one consisting of all plies oriented at 45°. A drop tower was used to impact structures at a range of energies, including energies above and below the threshold at which the aluminum layer was perforated. Numerical simulations were implemented using Sierra/SM, an in-house transient dynamics finite element code developed at Sandia National Laboratories. A Hosford plasticity model was used to describe the response of the aluminum layer. A newly implemented orthotropic continuum damage mechanics (CDM) constitutive model was used to represent the composite laminate. This 3D-CDM model was compared to a cohesive zone model (2D-CDM/CZM) to investigate efficacy of aluminum perforation energy prediction, delamination prediction, and computational cost. Accuracy of each model was evaluated using the experimental results. Each showed good agreement with the tests for both the force and velocity histories, as well as the observed damage mechanisms. The 2D-CDM/CZM model was marginally more accurate in capturing both the composite and aluminum behavior — this model averaged error percentages of -11.2% and 10.8% for residual velocity and peak force, respectively. Meanwhile, the 3D-CDM model predictions yielded average error percentages of -35.5% (velocity) and 22.6% (force). However, the 3D-CDM model generally resulted in a decreased computational cost; the average run time was 14% shorter than the 2D-CDM/CZM model and 3x as many timesteps per hour were computed using the same computational resources. In conclusion, new experimental data on the impact and perforation resistance of metal-composite laminates is presented in addition to numerical predictions of the impact behavior.

Carbon fiber↗
NASA NTRS1983

Space station needs, attributes and architectural options study costing working group briefing

The interface between tasks and the sequence of information flow are charted. The mission model and the requirements of each mission. These requirements along with the mission model schedule resulted in a further definition of the mission payloads, the Space Station architecture and the STS requirements was developed in task 2. The information was used to estimate the cost parameters necessary to generate cost estimates for the system with the aid of cost models for the Missions, Space Station and Space Transportation.

Source record↗
DOE OSTI2025

Interactive Gas Chemistry for Enhanced Science Capabilities of the Energy Exascale Earth System Model Version 3

Atmospheric chemistry plays a crucial role in Earth system models (ESMs), controlling atmospheric composition and radiative balance; it is highly interactive with the physical climate, biogeochemical cycles, and human systems. However, it often imposes computational challenges in an ESM. Here we develop a full troposphere‐stratosphere interactive chemistry module for the US Department of Energy's Energy Exascale Earth System Model (E3SM). We intentionally build a streamlined module based on E3SM version 2 that interacts with other components and maintains all of major chemical and chemistry‐climate feedbacks. The module incorporates a new, highly efficient tracer advection scheme; linearization of stratospheric chemistry; and abridged tropospheric chemical mechanism with 28 reactive tracers. This new model, E3SM‐chem, can readily perform century‐long climate simulations of ozone, methane, and nitrous oxide based on emission scenarios as well as provide hourly budgets for the gas‐phase radicals that drive aerosol chemistry. We evaluate E3SM‐chem with an atmosphere‐only simulation as in the recent climate model intercomparison project (CMIP6) finding results similar to the other CMIP6 models. For the present‐day, E3SM‐chem matches the standard measurement metrics for stratospheric and tropospheric ozone, surface air quality, other key reactive gases like carbon monoxide, and the methane lifetime. Overall, E3SM‐chem maintains the climate fidelity of the baseline model while adding at most 20% to the computational cost of the atmosphere model. Hence, interactive chemistry can be a default configuration for long climate simulations at resolutions of 1° or finer, which is crucial for producing self‐consistent chemistry‐climate feedbacks that alter the climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt

Abstract Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we describe a Bayesian active learning framework for autonomous “on-the-fly” training of fast and accurate reactive many-body force fields during molecular dynamics simulations. At each time-step, predictive uncertainties of a sparse Gaussian process are evaluated to automatically determine whether additional ab initio training data are needed. We introduce a general method for mapping trained kernel models onto equivalent polynomial models whose prediction cost is much lower and independent of the training set size. As a demonstration, we perform direct two-phase simulations of heterogeneous H 2 turnover on the Pt(111) catalyst surface at chemical accuracy. The model trains itself in three days and performs at twice the speed of a ReaxFF model, while maintaining much higher fidelity to DFT and excellent agreement with experiment.

42 ENGINEERING↗
DOE OSTI2020

Dynamic resource allocation drives growth under nitrogen starvation in eukaryotes

Cells can sense changes in their extracellular environment and subsequently adapt their biomass composition. Nutrient abundance defines the capability of the cell to produce biomass components. Under nutrient-limited conditions, resource allocation dramatically shifts to carbon-rich molecules. Here, we used dynamic biomass composition data to predict changes in growth and reaction flux distributions using the available genome-scale metabolic models of five eukaryotic organisms (three heterotrophs and two phototrophs). We identified temporal profiles of metabolic fluxes that indicate long-term trends in pathway and organelle function in response to nitrogen depletion. Surprisingly, our calculations of model sensitivity and biosynthetic cost showed that free energy of biomass metabolites is the main driver of biosynthetic cost and not molecular weight, thus explaining the high costs of arginine and histidine. We demonstrated how metabolic models can accurately predict the complexity of interwoven mechanisms in response to stress over the course of growth.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1980

FAME, a microprocessor based front-end analysis and modeling environment

Higher order software (HOS) is a methodology for the specification and verification of large scale, complex, real time systems. The HOS methodology was implemented as FAME (front end analysis and modeling environment), a microprocessor based system for interactively developing, analyzing, and displaying system models in a low cost user-friendly environment. The nature of the model is such that when completed it can be the basis for projection to a variety of forms such as structured design diagrams, Petri-nets, data flow diagrams, and PSL/PSA source code. The user's interface with the analyzer is easily recognized by any current user of a structured modeling approach; therefore extensive training is unnecessary. Furthermore, when all the system capabilities are used one can check on proper usage of data types, functions, and control structures thereby adding a new dimension to the design process that will lead to better and more easily verified software designs.

Rosenbaum, J. D.↗
NASA NTRSDate not supplied

Observations of Keyhole Porosity and Comparisons to Analytical Models for Ti-6Al-4V Powder Bed Fusion

Keyhole porosity defects are a common concern in powder bed fusion (PBF) processing. Keyhole porosity prediction models have generally fallen into two categories – high fidelity computational fluid dynamics simulations and low fidelity analytical or empirical models based on keyhole vibration dynamics. The low computational cost of low fidelity models allows them to better approach part-scale predictions. However, studies on low fidelity modeling techniques are limited by the lack of experimental data to assess the validity of the calibration over a wide range of processing conditions. This work extracts and quantifies keyhole porosity across 14 laser velocities, two laser powers, and six+ repetitions for a total of 176 independent trials. The measured porosity data are compared to low fidelity keyhole models to assess their success in predictive porosity occurrence. This work impacts the field by providing independent validation of keyhole porosity models for PBF for use in part-scale defect prediction.

powder bed fusion↗