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All sources NASA NTRS DOE OSTI

NASA NTRS2008

Strategic Analysis Overview

NASA s Constellation Program employs a strategic analysis methodology in providing an integrated analysis capability of Lunar exploration scenarios and to support strategic decision-making regarding those scenarios. The strategic analysis methodology integrates the assessment of the major contributors to strategic objective satisfaction performance, affordability, and risk and captures the linkages and feedbacks between all three components. Strategic analysis supports strategic decision making by senior management through comparable analysis of alternative strategies, provision of a consistent set of high level value metrics, and the enabling of cost-benefit analysis. The tools developed to implement the strategic analysis methodology are not element design and sizing tools. Rather, these models evaluate strategic performance using predefined elements, imported into a library from expert-driven design/sizing tools or expert analysis. Specific components of the strategic analysis tool set include scenario definition, requirements generation, mission manifesting, scenario lifecycle costing, crew time analysis, objective satisfaction benefit, risk analysis, and probabilistic evaluation. Results from all components of strategic analysis are evaluated a set of pre-defined figures of merit (FOMs). These FOMs capture the high-level strategic characteristics of all scenarios and facilitate direct comparison of options. The strategic analysis methodology that is described in this paper has previously been applied to the Space Shuttle and International Space Station Programs and is now being used to support the development of the baseline Constellation Program lunar architecture. This paper will present an overview of the strategic analysis methodology and will present sample results from the application of the strategic analysis methodology to the Constellation Program lunar architecture.

Cirillo, William M.↗

DOE OSTI2024

Hydrogen Hub Systems Analysis and Mapping Tool (ParaCraft) v1

A plug and play techno-economic analysis (TEA) and lifecycle assessment (LCA) tool was built that could incorporate new projects into the California ARCHES LLC Hydrogen hub, and generate results for the project, as well as the overall hub on an annual basis. The model was first constructed in Microsoft Excel and ArcGIS, but required labor intensive updating and manual decision making regarding the matching of hydrogen supplier and offtaker and estimation of transportation distances and utility sources. The project team converted the Excel model used for the ARCHES LLC hub conceptualization into a highly flexible and nearly completely automated R code. The R code runs the TEA and LCA, as well as provides mapping capabilities that automatically link projects by latitude and longitude to nearby utilities.

Breunig, Hanna↗

DOE OSTI2022

Microbial Curing of Cement for Energy Applications

Rutgers University, Lawrence Livermore National Laboratory, and the University of Arizona executed this program over 36 months with a 4-Task Program: (M1)-Microbial Engineering (M2)-Microstructure Modelling, (M3) Cement and Concrete Formulation, (M4)-Techno-economic analysis (TEA) and lifecycle assessment (LCA). This program developed a new carbonate cement concrete manufacturing process called microbial curing (MBC). MBC utilizes in-situ microbial production of CO 2 that dissolves into pore-bound water to carbonate a cementitious material creating a bonding matrix of CaCO 3 and SiO 2 that hardens and densifies the material. This is the first work of this type where calcium silicate was used in microbial studies. All other work reported in the literature always used a soluble form of calcium. This final report describes the work done in the final quarter, the best procedures and results, and the final techno-economic and lifecycle analyses. This quarter, we cast and cured twenty-five (4”x8”) cylinder samples. The compressive strength, split tensile, Young’s modulus, chloride permeability, and creep measurements were performed. These measurements demonstrated that MBC of calcium silicate concrete exhibits scaling problems due to the escape of ammonia gas, a product of the microbial reaction to generate CO 2 . As curing proceeds, the ability for the gas to escape from within the cylinder is restricted by the outer cylindrical portions densifying, making the outer portion highly impermeable to gas flow. In contrast, the small samples cured are uniformly cured, forming materials whose mechanical properties are 7x better than the large samples. This problem needs to be solved before this technology can be commercialized. The techno-economic and lifecycle analyses indicate that the technology developed in this program exhibits a significant opportunity to reduce the cost of cement and CO 2 emissions associated with concrete, provided the curing issue associated with larger samples can be addressed.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Retrofit Energy Analysis and Central Thermal modeling (REACT) v1.0

REACT is a website designed to simplify the analysis and decision-making process for retrofitting existing central plant heating and cooling systems with advanced heat pump technologies. The tool evaluates the technical and economic viability of replacing traditional boilers with various options including water-to-water or air-to-water heat pumps, which can provide efficient and lower-cost heating and cooling. It allows users to compare current central plant configurations with retrofit scenarios, assessing energy consumption, life-cycle costs, and environmental impact. Retrofitting traditional boiler and chiller systems with water-to-water or air-to-water heat pumps can significantly reduce energy consumption and lower lifecycle costs. The REACT provides: User-Friendly Tools: A user friendly web interface for quick, intuitive analysis accessible to non-experts. Advanced Modeling: A Python-powered engine for detailed parametric studies, optimization, and research applications. Comprehensive Analysis: Lifecycle cost evaluation, energy consumption modeling, and environmental impact assessment. Visual Insights: A variety of plots to visualize system performance and design trade-offs. The engine for the website (REACT) bases on several Python libraries, and the website will be hosted on an ETA server.

Kim, Donghun [Lawrence Berkeley National Laborator↗

NASA NTRS2017

The NASA Analogy Software Cost Model: A Web-Based Cost Analysis Tool

This paper provides an overview of the many new features and algorithm updates in the release of the NASA Analogy Software Cost Tool (ASCoT). ASCoT is a web-based tool that provides a suite of estimation tools to support early lifecycle NASA Flight Software analysis. ASCoT employs advanced statistical methods such as Cluster Analysis to provide an analogy based estimate of software delivered lines of code and development effort, a regression based Cost Estimating Relationships (CER) model that estimates cost (dollars), and a COCOMO II based estimate. The ASCoT algorithms are designed to primarily work with system level inputs such as mission type (earth orbiter vs. planetary vs. rover), the number of instruments, and total mission cost. This allows the user to supply a minimal number of mission-level parameters which are better understood early in the life-cycle, rather than a large number of complex inputs.

Hihn, Jairus↗

NASA NTRS2004

Terrestrial Planet Finder Coronagraph Optical Modeling

The Terrestrial Planet Finder Coronagraph will rely heavily on modeling and analysis throughout its mission lifecycle. Optical modeling is especially important, since the tolerances on the optics as well as scattered light suppression are critical for the mission's success. The high contrast imaging necessary to observe a planet orbiting a distant star requires new and innovative technologies to be developed and tested, and detailed optical modeling provides predictions for evaluating design decisions. It also provides a means to develop and test algorithms designed to actively suppress scattered light via deformable mirrors and other techniques. The optical models are used in conjunction with structural and thermal models to create fully integrated optical/structural/thermal models that are used to evaluate dynamic effects of disturbances on the overall performance of the coronagraph. The optical models we have developed have been verified on the High Contrast Imaging Testbed. Results of the optical modeling verification and the methods used to perform full three-dimensional near-field diffraction analysis are presented.

space telescopes↗

DOE OSTI2024

Methodology for Evaluating Commercial Energy Code Updates

This document lays out the Department of Energy’s (DOE’s) methodology for evaluating the cost-effectiveness of energy code and standard proposals and editions. The evaluation is applied to new provisions or editions of ANSI/ASHRAE/IES Standard 90.1 and the International Energy Conservation Code. The methodology follows standard lifecycle cost (LCC) economic analysis procedures. A cost-effectiveness evaluation requires three steps: 1) evaluating the energy and energy cost savings of code changes; 2) evaluating the incremental and replacement costs related to the changes; and 3) determining the cost-effectiveness of energy code changes based on those costs and savings over time.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Methodology for Evaluating Energy Savings, Cost-Effectiveness, and Societal Impacts of Commercial Energy Code Changes

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2000

Approximation Model Building for Reliability & Maintainability Characteristics of Reusable Launch Vehicles

This paper describes the development of parametric models for estimating operational reliability and maintainability (R&M) characteristics for reusable vehicle concepts, based on vehicle size and technology support level. A R&M analysis tool (RMAT) and response surface methods are utilized to build parametric approximation models for rapidly estimating operational R&M characteristics such as mission completion reliability. These models that approximate RMAT, can then be utilized for fast analysis of operational requirements, for lifecycle cost estimating and for multidisciplinary sign optimization.

Unal, Resit↗

NASA NTRS2023

NASA GRC ICME Schema for Materials Data Management: An Executive Summary

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

Materials↗

DOE OSTI2025

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Techno-Economic Evaluation of a 600MW Pumped Storage Hydropower Plant using the Pumped Storage Hydropower Valuation Tool

This paper presents a techno-economic evaluation of the proposed 600 MW, 8-hour Craig – Hayden pumped storage hydropower project using the U.S. Department of Energy’s Pumped Storage Hydropower Valuation Tool. The analysis integrates plant technical characteristics, regional grid conditions, and market-based operating assumptions to quantify stacked value streams from energy arbitrage, capacity, ancillary services, transmission congestion relief, and reliability. Both price taker and price influencer frameworks are applied to examine the impact of market participation and system interactions on lifecycle economic performance using Benefit - Cost Analysis and Multi - Criteria Decision Analysis. The results show that the price taker approach provides higher revenue estimates based on exogenous price signals, while the price influencer approach captures production cost savings, renewable curtailment reduction, and market price formation, yielding more conservative but system-representative outcomes. The study demonstrates the strategic value of long-duration PSH for enhancing operational flexibility, resource adequacy, and grid reliability in a high-renewable Western Interconnection.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗

DOE OSTI2025

A critical review and meta-analysis of energy demand, carbon footprint, and other environmental impacts from carbon fiber manufacturing

The demand for carbon fibers and carbon fiber-reinforced polymers (CFRPs) is rapidly growing due to their outstanding mechanical properties and potential to enhance sustainability, particularly for lightweighting applications. However, carbon fibers are typically produced from fossil-based feedstocks, involve energy-intensive processes, and have limited options for sustainable end-of-life management or circularity. Despite these challenges, the energy demand and lifecycle environmental implications of their production remain poorly understood. Here, we conduct a critical literature review and meta-analysis of carbon fiber manufacturing, revealing significant variations in reported energy demand, carbon footprint, and lifecycle inventory data. Our analysis makes two novel contributions. First, we identify key underlying factors driving these variations. Second, we highlight that carbon fiber, far from being a homogeneous product, has grades varying substantially in mechanical properties, end-use markets, energy intensity of manufacturing processes, and therefore environmental impacts—an aspect often underrepresented in life cycle assessments. We assert that current data are insufficient for reliably evaluating environmental impacts, posing a risk of misleading decision-making. Addressing this gap requires new lifecycle inventory datasets clearly incorporating carbon fiber heterogeneity and key influencing factors identified in this study. Additionally, we propose actionable recommendations, including a checklist, to advance sustainability in the carbon fiber sector.

CED↗

NASA NTRS2012

Navigation/Prop Software Suite

Navigation (Nav)/Prop software is used to support shuttle mission analysis, production, and some operations tasks. The Nav/Prop suite containing configuration items (CIs) resides on IPS/Linux workstations. It features lifecycle documents, and data files used for shuttle navigation and propellant analysis for all flight segments. This suite also includes trajectory server, archive server, and RAT software residing on MCC/Linux workstations. Navigation/Prop represents tool versions established during or after IPS Equipment Rehost-3 or after the MCC Rehost.

Bruchmiller, Tomas↗

NASA NTRS2015

Defining and Applying Limits for Test and Flight Through the Project Lifecycle GSFC Standard

The presentation will be given at the Annual Thermal Fluids Analysis Workshop (TFAWS 2015, NCTS 21070-15) hosted by the Goddard SpaceFlight Center (GSFC) Thermal Engineering Branch (Code 545). The powerpoint presentation details the process of defining limits throughout the lifecycle of a flight project.

Thermal↗

DOE OSTI2026

Admissible Powertrain Alternatives for Heavy-Duty Fleets: A Case Study on Resiliency and Efficiency

Heavy-duty vehicles dominate global freight movement and primarily rely on fossil-derived diesel fuel. However, fluctuations in crude oil prices and evolving emissions regulations have prompted interest in alternative powertrains to enhance fleet energy resiliency. This study paired real-world operational data from a large commercial fleet with high-fidelity vehicle models to evaluate the potential for replacing diesel internal combustion engine (ICE) trucks with alternative powertrain architectures. The baseline vehicle for this analysis is a diesel-powered ICE truck. Alternatives include ICE trucks fueled by bio- and renewable diesel, compressed natural gas (CNG) or hydrogen (H 2 ), as well as plug-in hybrid (PHEV), fuel cell electric (FCEV), and battery electric vehicles (BEV). While most alternative powertrains resulted in some payload capacity loss, the overall fleetwide impact was negligible due to underutilized payload capacity for the specific fleet considered in this study. For sleeper cab trucks, CNG-powered trucks achieved the highest replacement potential, covering 85% of the fleet. In contrast, H 2 and BEV architectures could replace fewer than 10% and 1% of trucks, respectively. Day cab trucks, with shorter daily routes, showed higher replacement potential: 98% for CNG, 78% for H 2 , and 34% for BEVs. However, achieving full fleet replacement would still require significant operational changes such as route reassignment and enroute refueling, along with considerable improvements to onboard energy storage capacity. Additionally, the higher total cost of ownership (TCO) for alternative powertrains remains a key challenge. This study also evaluated lifecycle impacts across various fuel sources, both fossil and bio-derived. Bio-derived synthetic diesel fuels emerged as a practical option for diesel displacement without disrupting operations. Conversely, H 2 and electrified powertrains provide limited lifecycle impacts under the current energy scenario. This analysis highlights the complexity of replacing diesel ICE trucks with admissible alternatives while balancing fleet resiliency, operational demands, and emissions goals. These results reflect a US-based fleet’s duty cycles, payloads, GVWR allowances, and an assumption of depot-only refueling/recharging. Applicability to other fleets and regions may differ based on differing routing practices or technical features such as battery swapping.

BEV↗

NASA NTRS1989

A system management methodology for building successful resource management systems

This paper presents a system management methodology for building successful resource management systems that possess lifecycle effectiveness. This methodology is based on an analysis of the traditional practice of Systems Engineering Management as it applies to the development of resource management systems. The analysis produced fifteen significant findings presented as recommended adaptations to the traditional practice of Systems Engineering Management to accommodate system development when the requirements are incomplete, unquantifiable, ambiguous and dynamic. Ten recommended adaptations to achieve operational effectiveness when requirements are incomplete, unquantifiable or ambiguous are presented and discussed. Five recommended adaptations to achieve system extensibility when requirements are dynamic are also presented and discussed. The authors conclude that the recommended adaptations to the traditional practice of Systems Engineering Management should be implemented for future resource management systems and that the technology exists to build these systems extensibly.

Hornstein, Rhoda Shaller↗

NASA NTRS2018

How Do You Go From a Concept Idea to a NASA Selected Mission? Formulating the Psyche Discovery Mission with JPL's Concurrent Engineering Teams

JPL’s Office of Formulation provides continuity of support and access to domain subject matter experts, as Principal Investigators mature their mission concepts from “cocktail napkin” ideas to Preliminary Design Reviews [1]. Using NASA’s Psyche mission as a case study, we will describe JPL’s concurrent engineering ATeam and Team X support to the Psyche competed concept study team in the areas of 1) Science Feasibility, 2) Trade Space Exploration, 3) Spacecraft Point Design and Cost Estimate, 4) Science, Technical, Management, and Cost Review, and 5) Strategy and Communication Development. NASA’s Psyche Discovery class mission started as a grassroots idea in our A-Team facility, and in less than five years was selected as a mission under NASA’s Discovery Program. While Psyche had a dedicated concept development team [2], they utilized JPL’s concurrent engineering teams, methods, analysis tools, and experts throughout their mission concept lifecycle.

Ziemer, John↗