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DOE OSTI2024

Model-Based Energy and Cost Analysis of Direct Air Capture Using ePTFE-Based Laminate-Structured Gas–Solid Contactors

Carbon dioxide removal (CDR) technologies will play a significant role in limiting global warming if implemented on a large scale. Direct air capture (DAC) is a scalable approach for removing atmospheric carbon, yet the true scope of its scalability remains unclear due to the early stage of technology development and high first plant costs. This study provides groundwork for understanding the technoeconomic trade-offs in developing DAC systems using laminate-structured gas–solid contactors, encompassing the analysis of both contactor and process design spaces. The robust mass transfer and process models outlined in this study provide tools for evaluating DAC processes and designing DAC plants based on cost and energy analysis. First, the key contactor geometrical parameters are identified to understand the CO 2 productivity–energy demand trade-offs, where geometries yielding higher mass transfer rates can achieve higher CO 2 productivities at the expense of energy consumption by fans and steam use. Next, a detailed process parametric study is conducted for DAC systems coupled with steam-assisted temperature-vacuum swing adsorption (S-TVSA) to visualize the trade-offs in the multidimensional design space. The main cost driver dramatically changes over different process conditions, but the operating cost prevailed on the Pareto front, with potential to operate as low as 150 $/tonne-CO 2 (within the cost range of 148–504 $/tonne-CO 2 in this study where the DAC system is coupled with industrial facilities for steam production).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Microwave Cavity Simulation Using Ansys HFSS

The design of microwave cavity detectors for axion dark matter research is often accomplished using advanced full-wave electromagnetic simulation software tools. These tools provide a cost-effective approach to evaluate a wide variety of cavity configurations, frequency tuning mechanisms, and conductive or dielectric materials and coatings. One simulation software package used for this application is Ansys High Frequency Structure Simulator (HFSS), which is based upon the well-established finite element method. HFSS includes numerous features useful for microwave cavity design such as parametric geometry modeling, adaptive meshing algorithm, curvilinear mesh elements, driven modal and eigenmode matrix solvers, and optimization algorithms. This paper describes the use of the HFSS software to simulate microwave cavities for axion haloscope detectors, with an example tutorial for a cylindrical cavity. Excellent agreement between the simulated and analytical results is shown for the resonant frequency, quality factor, and form factor.

Ansys HFSS, Cavity simulation, finite element mode↗

DOE OSTI2023

BEopt™ (Building Energy Optimization Tool) version 3.0.1 3/16/2023 [SWR-05-41]

The BEopt™ (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy. The BEopt software can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations. The BEopt software provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated. The BEopt software uses EnergyPlus®, the Department of Energy's flagship simulation engine. Simulation assumptions are based on ANSI/RESNET/ICC Standards and the Building America Housing Simulation Protocols. The sequential search optimization technique used by the BEopt software: Finds minimum-cost building designs at different target energy-savings levels Identifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference. Download A BEopt™ Version 3.0.1 Beta release (Mar. 16, 2023) is now available. Download the BEopt 3.0.1 Beta setup file.

Christensen, Craig↗

NASA NTRS2017

Norton-Thevenin Receptance Coupling (NTRC) as a Payload Design Tool

The NASA Engineering and Safety Center (NESC) is funding a study to develop an alternate method for performing coupled loads analysis called Norton-Thevenin Receptance Coupling (NTRC). NTRC combines Receptance Coupling (RC), a frequency-domain synthesis method and Norton-Thevenin (NT) theory, an impedance based approach for simulating the interaction between dynamic systems. The goal of developing the NTRC method is to provide a tool that payload developers can use to reduce the conservatism in defining preliminary design loads, assess the impact of design changes between formal load cycles, and to perform trade studies for design optimization with a minimum amount of data required from the launch vehicle (LV) provider. NTRC also has the ability to perform parametric loads analysis where many different design configurations can be evaluated. This will result in cost and schedule benefits to the payload developer that are currently not possible under the standard coupled loads analysis (CLA) flow where typically only 2-3 official load cycles are performed by the LV provider over the life of a payload program. NTRC is not envisioned as a replacement for the official load cycles performed by the LV provider but rather as a means to address the types of design issues faced by the payload developer before and between official load cycles.The presentation provides an overview of the NTRC methodology and discusses how NTRC can be used to replicate the results from a standard LV CLA. The presentation covers the benchmarking that has been performed as part of the NESC study to demonstrate the accuracy of the technique for both frequency and time domain dynamic analyses. Future plans for benchmarking the NTRC approach against CLA results for NASAs Space Launch System (SLS) and commercial launch vehicles are discussed and the role that NTRC is envisioned to play in the payload development cycle.

Structural Dynamics↗

DOE OSTI2020

Monte Carlo characterization of the cosmic ray muon flux in shallow subsurface geological repositories intended for disposal of radioactive materials

Recent challenges in monitoring subsurface geological repositories intended for disposal of radioactive materials such as spent nuclear fuel call for new, innovative concepts that are facility independent, cost-effective, passive, and reliable. Once nuclear material is in place at these facilities, reverifying the inventory may no longer be feasible if continuity of knowledge is lost or unavailable to the inspectors. Using cosmic ray muons may present several potential advantages over conventional photon/neutron signatures, and their use in safeguards applications have only received attention in the past decade. However, there have been limited efforts to explore the integration of cosmic ray muons into repository safeguards and study potential gains, risks, and costs. This paper presents a Monte Carlo-based methodology to characterize the cosmic ray muon flux, including muon angular and energy differential distributions at depths representative of subsurface geological repositories. Since there have been limited measurements at these sites and a measurement made in one site is not always transferable to another site, the objective is to develop an efficient simulation method and useful parametrizations to provide a convenient tool for enabling muon simulations at any geological repository site. It is expected these results will provide a better understanding of how muons can be integrated into an existing geological repository safeguards framework.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2018

Norton-Thevenin Receptance Coupling (NTRC) as a Payload Analysis Tool

The NASA Engineering and Safety Center (NESC) has funded a study of a new method formulated by NASA Engineers called Norton-Thevenin Receptance Coupling (NTRC) to perform coupled loads analysis (CLA). The problem that NTRC attempts to solve is the dependency of the payload organization to high CLA costs, long schedules, lack of standard capabilities to evaluate multiple configurations and unavailability of loads when needed. NTRC solves the problem by providing a tool that payload developers can use to obtain loads at a fraction of the cost of a CLA at any time that it is required. While NTRC is not intended to replace the formal load cycles performed by the launch vehicle (LV) provider, it will provide the ability to reduce the conservatism in defining preliminary design loads, assess the impact of design changes between formal load cycles, perform trade studies and perform parametric loads analysis where many different design configurations can be evaluated with a minimum amount of data required from the LV provider. NTRC condenses all the necessary information into the launch vehicle to payload/s connection points or boundary degrees of freedom (BD). The launch vehicle model is represented by its impedance at its BDs; its forcing functions are represented by the acceleration at those BDs when the payload is absent and the latter is represented by its impedance at the same BDs. Payload responses are represented by transfer functions of selected response to interface BDs. The methodology has contributed to the Loads and Dynamics discipline advancement and successfully passed Peer Reviews. NTRC is exact in the frequency domain. Time domain replication and accuracy is outstanding. A second phase is envisioned to benchmark the whole set of CLA events for the Agency's most utilized Launch Vehicles, and ready it for operational deployment at NASA.

Kaufman, Daniel↗

DOE OSTI2025

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

Model ensembles are effective tools for estimating prediction uncertainty in deep learning atomistic force fields. However, their widespread adoption is hindered by high computational costs and overconfident error estimates. In this work, we address these challenges by leveraging distributions of per-sample errors obtained during training and employing a distance-based similarity search in the model latent space. Our method, which we call LTAU (Loss Trajectory Analysis for Uncertainty), efficiently estimates the full probability distribution function of errors for any test point using the logged training errors, achieving speeds that are 2–3 orders of magnitudes faster than typical ensemble methods and allowing it to be used for tasks where training or evaluating multiple models would be infeasible. We apply LTAU towards estimating parametric uncertainty in atomistic force fields (LTAU-FF), demonstrating that it produces well-calibrated confidence intervals and predicts errors that correlate strongly with the true errors for data near the training domain. Furthermore, we show that the errors predicted by LTAU-FF can be used in practical applications for detecting out-of-domain data, tuning model performance, and predicting failure during simulations. We believe that LTAU will be a valuable tool for uncertainty quantification in atomistic force fields and is a promising method that should be further explored in other domains of machine learning.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Lunar lander configuration study and parametric performance analysis

Future Lunar exploration plans will call for delivery of significant mounts or cargo to provide for crew habitation, surface tansportation, and scientific exploration activities. Minimization of costly surface based infrastructure is in large part directly related to the design of the cargo delivery/landing craft. This study focused on evaluating Lunar lander concepts from a logistics oriented perspective, and outlines the approach used in the development of a preferred configuration, sets forth the benefits derived from its utilization and describes the missions and system considered. Results indicate that only direct-to-surface downloading of payloads provides for unassisted cargo removal operations imperative to efficient and low risk site buildup, including the emplacement of Space Station derivative surface habitat modules, immediate cargo jettison for both descent abort and emergency surface ascent essential to piloted missions carrying cargo, and short habitat egress/ingress paths necessary to productive surface work tours for crew members carrying hand held experiments, tools and other bulky articles. Accommodating cargo in a position underneath the vehicles structural frame, landing craft described herein eliminate altogether the necessity for dedicated surface based off-loading vehicles, the operations and maintenance associated with their operation, and the precipitous ladder climbs to and from the surface that are inherent to traditional designs. Parametric evaluations illustrate performance and mass variation with respect to mission requirements.

Donahue, Benjamin B.↗

NASA NTRS2000

Engine System Loads Development for the Fastrac 60K Flight Engine

Frady, Greg↗

NASA NTRS2002

Engine System Loads Analysis Compared to Hot-Fire Data

Early implementation of structural dynamics finite element analyses for calculation of design loads is considered common design practice for high volume manufacturing industries such as automotive and aeronautical industries. However with the rarity of rocket engine development programs starts, these tools are relatively new to the design of rocket engines. In the NASA MC-1 engine program, the focus was to reduce the cost-to-weight ratio. The techniques for structural dynamics analysis practices, were tailored in this program to meet both production and structural design goals. Perturbation of rocket engine design parameters resulted in a number of MC-1 load cycles necessary to characterize the impact due to mass and stiffness changes. Evolution of loads and load extraction methodologies, parametric considerations and a discussion of load path sensitivities are important during the design and integration of a new engine system. During the final stages of development, it is important to verify the results of an engine system model to determine the validity of the results. During the final stages of the MC-1 program, hot-fire test results were obtained and compared to the structural design loads calculated by the engine system model. These comparisons are presented in this paper.

Frady, Gregory P.↗

DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗

NASA NTRS1977

Parametric study of transport aircraft systems cost and weight

The results of a NASA study to develop production cost estimating relationships (CERs) and weight estimating relationships (WERs) for commercial and military transport aircraft at the system level are presented. The systems considered correspond to the standard weight groups defined in Military Standard 1374 and are listed. These systems make up a complete aircraft exclusive of engines. The CER for each system (or CERs in several cases) utilize weight as the key parameter. Weights may be determined from detailed weight statements, if available, or by using the WERs developed, which are based on technical and performance characteristics generally available during preliminary design. The CERs that were developed provide a very useful tool for making preliminary estimates of the production cost of an aircraft. Likewise, the WERs provide a very useful tool for making preliminary estimates of the weight of aircraft based on conceptual design information.

Beltramo, M. N.↗

DOE OSTI2020

Sensitivity Analysis and Effective Parametrization of PEM Fuel Cell Models

The cost of proton-exchange-membrane fuel cells (PEMFCs) remains a major hurdle in large-scale commercialization of this technology. To improve their performance and reduce cost, novel materials and electrode designs are continuously envisioned, e.g., non-PGM catalyst layers, ultra-thin Pt/Pt-Ni based catalyst layers, structured ionomer arrays or NSTF catalyst layers.1 Understanding the impact of these improvement strategies can be extremely time and cost intensive due to complex physical phenomena and large design space. We have previously developed a PEMFC modeling framework2 which has been a time and cost effective tool for understanding and optimizing the complex multi-physics phenomena within PEMFCs; however, several of the cell parameters used in the modeling have large spread in measured data.3 Furthermore, several transport parameters such as water adsorption kinetics have not been accurately measured and the approximations are spread over several orders of magnitude. These uncertainties cause problems in ascertaining accuracy of the modeling approach and they reduce the predictive power of the numerical models. The aim of this work is to identify the sensitivity of PEFC numerical model outputs to various input parameters. The previously in-house developed MEA modeling framework2 is used for PEMFC modeling. The sensitivity of the model outputs with respect to inputs parameters is obtained by analyzing the condition numbers for different output-input pairs at varying operating conditions. An example of the sensitivity analysis is shown in Figure 1. The condition numbers are obtained for the entire possible range of input parameters at varying operating conditions to identify the most crucial parameters of the PEMFC model. Based on our preliminary analysis, parameters related to kinetics (exchange current density and ECSA) and heat/water management in electrodes and ionomer (ionomer fraction, thermal conductivity) are most crucial. One of the major goals of this work is to identify the most crucial set of parameters towards which the model shows maximum sensitivity. This will guide future experimentalists to measure these properties with higher accuracy. Furthermore, the sensitivity analysis will also enable us to optimize the PEMFC performance by selectively targeting the most sensitive parameters and thereby making the largest impact. Acknowledgements The work is funded under the Fuel Cell Performance and Durability Consortium (FC-PAD), by the Fuel Cell Technologies Office (FCTO), Office of Energy Efficiency and Renewable Energy (EERE), of the U.S. Department of Energy under contract number DE-AC02-05CH11231. The authors would like to thank Nathan Craig at Robert Bosch LLC for his valuable input in designing the sensitivity analysis. The authors would also like to thank Giovanna Bucci and Matthias Hanauer at Robert Bosch for their valuable inputs and discussion. References P. K. Sinha, W. Gu, A. Kongkanand and E. Thompson, J. Electrochem. Soc., 158, B831 (2011). L. M. Pant, M. R. Gerhardt, N. Macauley, R. Mukundan, R. L. Borup and A. Z. Weber, Electrochim. Acta, 326, 134963 (2019). R. Vetter and J. O. Schumacher, ArXiv181110091 Phys. (2018). Figure 1

Pant, Lalit↗

DOE OSTI2022

Need for advanced research reactors for the next-generation reactor physics, analysis tools, and technology

Full text of publication follows. There is an urgent need for design and deployment of advanced research and test reactors in support of design, licensing and operation of advanced power reactors and education of next generation nuclear workforce. Existing research reactors mostly were designed and constructed decades ago with the main objectives of training operators, performing reactor physics experiments, and educating nuclear engineers and scientists. There are already gaps and significant concern about future capabilities for the existing research reactor facilities to address modern instrumentation and/or flexible environments for: performing reactor physics studies for advanced designs which have significantly different core materials forms and compositions, reactor shapes and size; validation of advanced high-fidelity software; development of machine learning algorithms for enhancement of human-machine collaboration in support of reactor monitoring, operation and safeguards; and, effective education of the next-generation workforce. The authors will focus on the need for advanced research reactors to improve and validate fast and accurate simulation tools for high-fidelity modeling and analysis of nuclear reactors in support of their design, optimization, licensing, operation, and monitoring. In the past, simulation tools were limited to relatively coarse models using approximate methodologies that benefited from two main factors: i) allowance for large margins and tolerances; ii) ability to construct prototype (e.g., zero power) reactors for adjustment of approximate methodologies. The next generation reactors have to be designed mainly by using novel high-fidelity computational tools that are accurate and fast, and therefore can be used for parametric studies and uncertainty quantification. To sufficiently demonstrate the accuracy of these tools, advanced research reactors are needed. The authors argue the need for new computational paradigms such as the MRT (Multistage, Response- function Transport) methodology which has resulted in the development of the novel high-fidelity RAPID (Real-time Analysis for Particle-transport and In-situ Detection) code system. Such code systems have to be robust in modeling any complex system, and should be fast and accurate, henceforth their uncertainties can be quantified at reasonable costs. Again, advanced research reactors are needed for the validation of the fidelity and accuracy of new computational tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2016

Improving and Expanding NASA Software Cost Estimation Methods

Estimators and analysts are increasingly being tasked to develop better models and reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods for cost estimation, there is very little focus on the use of cost models based on analogy and clustering algorithms. In this paper we summarize the results of our research in developing an analogy method for estimating NASA spacecraft flight software using spectral clustering on system characteristics (symbolic nonnumerical data) and evaluate its performance by comparing it to a number of the most commonly used estimation methods. The strengths and weaknesses of each method based on their performance are also discussed. The paper concludes with an overview of the analogy estimation tool (ASCoT) developed for use within NASA that implements the recommended analogy algorithm.

Hihn, Jairus↗

NASA NTRS2023

EVA Task and 3D Pose Recognition from Video

Extravehicular Activity (EVA) has been known to involve potential risks of biomechanical stresses and injuries to crewmembers. Gathering of EVA motion patterns is necessary for risk analysis and mitigation. However, many existing techniques, such as motion capture systems, are not only cost-prohibitive but are impractical for retrospective analysis of past missions. In this work, a software tool was developed, which can estimate the 3D poses of a spacesuit from photographs or videos, without using special sensors or equipment. The tool is based on the state-of-the-art artificial intelligence and machine learning (AI/ML) system, which was trained by studying and capturing motion patterns of past and current spacesuit test data. The AI/ML tool was further enhanced using synthetically generated data, in which the suit postures, backgrounds, camera angles and illumination conditions were parametrically adjusted and rendered for training. The tool, incorporated the methodologies of Convolutional Neural Network (CNN), was trained, and tested in the cloud computing environment. The trained model was then applied on new imagery and video to extract estimated joint positions and suit outlines. The joint positions were further processed to capture activity (“digging”), pose labels (“bending”), and other useful downstream information. The model performance on new imagery and video was successfully assessed for accuracy and reliability. This AI/ML based posture recognition tool thus allows for the quantification of injury risk and task performance characterization for both current and past missions and training, which can immensely help to improve EVA task and suit design.

Kyung Han Kim↗

NASA NTRS2014

Latest NASA Instrument Cost Model (NICM): Version VI

The NASA Instrument Cost Model, NICM, is a suite of tools which allow for probabilistic cost estimation of NASA's space-flight instruments at both the system and subsystem level. NICM also includes the ability to perform cost by analogy as well as joint confidence level (JCL) analysis. The latest version of NICM, Version VI, was released in Spring 2014. This paper will focus on the new features released with NICM VI, which include: 1) The NICM-E cost estimating relationship, which is applicable for instruments flying on Explorer-like class missions; 2) The new cluster analysis ability which, alongside the results of the parametric cost estimation for the user's instrument, also provides a visualization of the user's instrument's similarity to previously flown instruments; and 3) includes new cost estimating relationships for in-situ instruments.

Mrozinski, Joe↗

NASA NTRS2016

A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

Suboptimal suit fit is a known risk factor for crewmember shoulder injury. Suit fit assessment is however prohibitively time consuming and cannot be generalized across wide variations of body shapes and poses. In this work, we have developed a new design tool based on the statistical analysis of body shape scans. This tool is aimed at predicting the skin deformation and shape variations for any body size and shoulder pose for a target population. This new process, when incorporated with CAD software, will enable virtual suit fit assessments, predictively quantifying the contact volume, and clearance between the suit and body surface at reduced time and cost.

Kim, K. Han↗