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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 1,009 records · Page 56

Designers' unified cost model

The Structures Technology Program Office (STPO) at NASA LaRC has initiated development of a conceptual and preliminary designers' cost prediction model. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state-of-the-art preliminary design tools and computer aided design programs is being evaluated. The goal of this task is to establish theoretical cost functions that relate geometric design features to summed material cost and labor content in terms of process mechanics and physics. The output of the designers' present analytical tools will be input for the designers' cost prediction model to provide the designer with a database and deterministic cost methodology that allows one to trade and synthesize designs with both cost and weight as objective functions for optimization. This paper presents the team members, approach, goals, plans, and progress to date for development of COSTADE (Cost Optimization Software for Transport Aircraft Design Evaluation).

Freeman, W.↗

MarpoDB: An open registry for Marchantia polymorpha genetic parts

Marchantia polymorpha is an extant relative of the earliest terrestrial plants and has attracted a substantial interest as a model organism for evolutionary and developmental studies. Given its relatively simple genome, compact gene families, simple morphology, ease of propagation and transformation, M. polymorpha is becoming a promising platform for plant synthetic biology. Modular genetic parts have been essential for development of synthetic biology approaches, so we sought to design an engineering oriented database for M. polymorpha genetic parts where each gene is a standalone functional unit. MarpoDB is a database of M. polymorpha genes and genetic parts, which is tailored to become an integral tool for a synthetic biology workflow. Among its features are precompiled cross-database querying to InterPro, Pfam signatures and non-redundant Viridiplantae BLAST annotations; BLAST querying to M. polymorpha genes; sequence export in GenBank format; recoding of sequences to the common syntax for type IIS assembly and exchange of DNA parts; and a minimalistic, intuitive and interactive user interface for gene models and sequence exploration. Furthermore, we have implemented user input to encourage feedback, collaboration and exchange between the MarpoDB community. MarpoDB source-code is released on GitHub to promote development of computational tools for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

A complementarity-based vapor-liquid equilibrium formulation for equation-oriented simulation and optimization

Vapor-Liquid Equilibrium (VLE) is a cornerstone of computer aided process engineering (CAPE). Embedded within process system models, VLE calculations are inherently procedural with non-smooth behavior that frequently require discrete decisions. Traditionally, these features resist the incorporation of VLE within efficient, large-scale equation-oriented (EO) process simulation and optimization strategies. On the other hand, recent reformulation of VLE models through the incorporation of complementarity constraints has broadened its scope to deal seamlessly with phase transitions and even supercritical excursions in process simulation and optimization. In this study, we extend these VLE complementarity models to EO frameworks where procedural thermodynamic property libraries are still required. Here, we develop an efficient, non-intrusive, and intuitive “square-flash” equation system that has been implemented within the IDAES Integrated Platform (IDAES-IP). Further, the effectiveness of this modular approach is demonstrated on case studies for non-ideal flash calculations and distillation optimization with disappearing phases and supercritical transitions.

97 MATHEMATICS AND COMPUTING↗

Water desalination through the dewpoint evaporative system

This paper presents the first numerical analysis of a novel Dew Point Desalination unit (DPD), which utilizes the phenomenon of the evaporative cooling process to minimize energy consumption. The proposed solution is based on a modular structure, which allows it to obtain any required water production capacity. The analyses for various operational parameters and various climatic conditions are based on the numerical simulations conducted using a validated mathematical model. The system performance was described with different factors, including specific energy consumption (SEC) and daily water production rate respected to 1 m^3*s^-1 of passing air stream (DWP). It is shown that the DPD system can operate in almost every climate zone, and the desalinated water production consumes less than 1.5 kWh*m^-3 of electric energy It is noted the best performance of the DPD system is achieved in the semi-arid, desert and subtropical climate zones. In these climate zones, the 2-stage DPD system allows the production of desalinated water with an electric energy consumption SEC lower than 0.5 kWh*m^-3. The additional benefit of the DPD system is its modularity. The presented DPD system stands as a module, that can be multiplied as needed to achieve the desired size of the desalination plant.

Desalination↗

Finned-tube-integrated modular thermal storage systems for HVAC load modulation in buildings

While there is considerable focus on latent-based thermal energy storage (TES) systems, the low thermal conductivity of phase change materials (PCMs) remains a critical concern. Many approaches to enhance PCM conductivity either require complicated synthesis processes or are cost prohibitive. In this study, we investigate finned-tube modular TES systems, which are simple in design, easy to manufacture, and cost-effective due to their standard materials and components. The study includes detailed modeling and experimentation of two devices containing similar amounts of PCM but different fin spacings. The study reveals that having more fins does not necessarily increase the TES thermal performance because the reduction in the PCM volume fraction can reduce the TES volumetric and specific energy densities. We find that larger fin spacings provide a higher specific energy for lower C rates (<1C), while smaller fin spacings provide a higher specific energy for higher C rates (>1C).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Numerical Simulation of Isothermal Flow Across Slant Five-Tube Bundle with Spectral Element Method Code Nek5000

The helical coil steam generator (HCSG) is a specific type of shell-and-tube heat exchanger known for having a higher heat transfer coefficient than many other designs. For this reason, they are considered in small modular reactor and high temperature reactor designs. Investigation of flow behavior in HCSGs is important for better design. In this paper we present our study for modeling the coolant flow in the primary side of the HCSG. We used Nek5000, an open source, high-order spectral element computational fluid dynamics code developed in Argonne National Laboratory. Nek5000 accepts only hexahedral mesh, which makes the meshing process for the complicated HCSG geometry very challenging. A tetrahedral-to-hexahedral meshing strategy was applied to bypass the geometric complexities. In this study large eddy simulation (LES) was performed at the Reynolds number of 9000 based on the inlet velocity and the tube diameter. The employed subgrid-scale model for LES relies on explicit filtering. First- and second-order statistics were compared to available experimental data. We report overall velocity and turbulent kinetic energy showed good agreement with particle image velocimetry data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Sensitivity study with a $\textit{D}$ and $\textit{B}$ mesons modular simulation code of heavy flavor $R_{AA}$ and azimuthal anisotropies based on beam energy, initial conditions, hadronization, and suppression mechanisms

Heavy flavor probes provide important information about the in-medium properties of the quark-gluon plasma produced in heavy-ion collisions. In this work, we investigate the effects of 2D + 1 event-by-event fluctuating hydrodynamic backgrounds on the nuclear suppression factor and momentum anisotropies of heavy flavor mesons and nonphotonic electrons. Using the state-of-the-art $\textit{D}$ and $\textit{B}$ mesons modular simulation code (called “DAB-MOD”), we perform a systematic comparison of different transport equations in the same background, including a few energy-loss models—with and without energy-loss fluctuations—and a relativistic Langevin model with different drag parametrizations. We present the resulting $\textit{D}$ and $\textit{B}$ mesons $R_{A A}, v_2, v_3,$ and $v_4$ as well as multiparticle cumulants, in AuAu collisions at $\sqrt{s_{NN}}$ = 200 GeV and PbPb collisions at $\sqrt{s_{NN}}$ = 2.76 TeV and $\sqrt{s_{NN}}$ = 5.02 TeV , and compare them to the available experimental data. The $v_2${4}/$v_2${2} ratio, which is known to be a powerful probe of the initial conditions and flow fluctuations in the soft sector, is also studied in the context of heavy flavor. We also investigate the correlations between the transverse anisotropies of heavy mesons and all charged particles to better understand how heavy quarks couple to the hydrodynamically expanding quark-gluon plasma. Finally, we study the influence that different initial conditions and the implementation of heavy-light quark coalescence has on our results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows

In the past couple of years, there has been a proliferation in the use of machine learning approaches to represent subgrid-scale processes in geophysical flows with an aim to improve the forecasting capability and to accelerate numerical simulations of these flows. Despite its success for different types of flow, the online deployment of a data-driven closure model can cause instabilities and biases in modeling the overall effect of subgrid-scale processes, which in turn leads to inaccurate prediction. To tackle this issue, we exploit the data assimilation technique to correct the physics-based model coupled with the neural network as a surrogate for unresolved flow dynamics in multiscale systems. In particular, we use a set of neural network architectures to learn the correlation between resolved flow variables and the parametrizations of unresolved flow dynamics and formulate a data assimilation approach to correct the hybrid model during their online deployment. We illustrate our framework in a set of applications of the multiscale Lorenz 96 system for which the parametrization model for unresolved scales is exactly known, and the two-dimensional Kraichnan turbulence system for which the parametrization model for unresolved scales is not known a priori. Our analysis, therefore, comprises a predictive dynamical core empowered by (i) a data-driven closure model for subgrid-scale processes, (ii) a data assimilation approach for forecast error correction, and (iii) both data-driven closure and data assimilation procedures. We show significant improvement in the long-term prediction of the underlying chaotic dynamics with our framework compared to using only neural network parametrizations for future prediction. Moreover, we demonstrate that these data-driven parametrization models can handle the non-Gaussian statistics of subgrid-scale processes, and effectively improve the accuracy of outer data assimilation workflow loops in a modular nonintrusive way.

42 ENGINEERING↗

HDU Pressurized Excursion Module (PEM) Prototype Systems Integration

The Habitat Demonstration Unit (HDU) project team constructed an analog prototype lunar surface laboratory called the Pressurized Excursion Module (PEM). The prototype unit subsystems were integrated in a short amount of time, utilizing a skunk-works approach that brought together over 20 habitation-related technologies from a variety of NASA centers. This paper describes the system integration strategies and lessons learned, that allowed the PEM to be brought from paper design to working field prototype using a multi-center team. The system integration process included establishment of design standards, negotiation of interfaces between subsystems, and scheduling fit checks and installation activities. A major tool used in integration was a coordinated effort to accurately model all the subsystems using CAD, so that conflicts were identified before physical components came together. Some of the major conclusions showed that up-front modularity that emerged as an artifact of construction, such as the eight 45 degree "pie slices" making up the module whose steel rib edges defined structural mounting and loading points, dictated much of the configurational interfaces between the major subsystems and workstations. Therefore, 'one of the lessons learned included the need to use modularity as a tool for organization in advance, and to work harder to prevent non-critical aspects of the platform from dictating the modularity that may eventually inform the fight system.

Gill, Tracy R.↗

HabSim: A Modular Coupled Virtual Testbed for Simulating ExtraTerrestrial Habitat Systems

Extraterrestrial habitats involve a tightly coupled combination of hardware, software, and humans while operating in an unforgiving environment that poses many risks, both anticipated and unanticipated. Traditional approaches with such systems of systems focus on reliability, robustness, and redundancy. These approaches seek to avoid failure rather than reduce overall risk. However, faults are inevitable, and understanding and managing the complex and emergent behavior and cascading events of such a complex system is critical. This study describes the development of HabSim, a computational simulation environment intended to support research to establish the know-how to design and operate resilient and autonomous SmartHabs. HabSim is a modular virtual testbed composed of many of the coupled dynamic systems expected in a typical SmartHab. A heterogeneous set of interconnected physics-based and phenomenological models is used to represent the essential functions of a SmartHab. HabSim further considers disruptions and models damage and repair of certain components. This paper discusses a) system and subsystem requirements of the deep space habitat included in the HabSim platform; b) architectural choices made in response to the requirements; c) technical considerations for developing, verifying, configuring, and executing HabSim; and d) illustrative sample results from a simulation of a representative disruption scenario.

Mohsen Azimi↗

MPACT Safeguards Modeling: FY25 Update

Sandia National Laboratories develops and maintains several open-source software packages to support material accountancy analyses. This includes the Material Accountancy Performance Indicator Toolkit (MAPIT), the Fissile Facility Flow Modeler (F3M) and the Separation and Safeguards Performance Model Library (SSPM-L). MAPIT is responsible for performing statistical safeguards analyses on bulk and itemized data from nuclear fuel cycle facilities and can operate on real or synthetic data. MAPIT is the only open-source software for such analyses. F3M is a library of modules, built in MATLAB Simulink, that contain pre made blocks to represent different generic fuel cycle processes. These blocks can be used together in a modular fashion to represent and simulate nuclear fuel cycle processes with the goal of improving facility-level accountancy during the design phase. F3M is also an open-source library. Finally, the SSPM-L library is a series of completed models built from F3M. The library includes facility models such as a generic PUREX facility and a fuel fabrication facility. The SSPM-L library is not open source, but is available to collaborators with a relevant use case. These tools include modeling and simulation pipelines to simulate nuclear fuel cycle facilities and the underlying software needed to simulate measurement uncertainty and perform statistical analyses. Together, these tools can perform end-to-end nuclear material accountancy analyses. This report documents the various improvements made to these tools in FY25. Specifically, we added new statistical test, new statistical modeling capabilities, new fuel cycle facility models, and launched a new open-source model component library.

97 MATHEMATICS AND COMPUTING↗

Building Efficiency Targeting Tool for Energy Retrofits (BETTER) Web Application (BETTER Web App) v1.0

The Building Efficiency Targeting Tool for Energy Retrofits (BETTER) V.1.0 web application identifies cost-saving energy and emissions reductions in buildings and portfolios, without site visits or complex modeling. With minimal data entry, BETTER benchmarks a building's or portfolio's energy use against peers; quantifies energy, cost, and greenhouse gas (GHG) reduction potential; and recommends energy efficiency measures for individual buildings or portfolios, targeting specific energy savings levels. The source code of BETTER's modular, cross-platform analytical engine has previously been disclosed (2019-001) and is available on GitHub and can be adopted, redeveloped, and redistributed freely under an open-source license, allowing users to incorporate BETTER's analytical capabilities into their own software platforms and tools. The BETTER V.1.0 web application, developed with the Django web-framework and the Model-View-Controller (MVC) architecture being disclosed here, provides a graphical user interface (GUI) for any user to view the software tutorials, download and upload a data entry template, configure and run the BETTER analyses, and view the final analytical reports.

Szum, Carolyn↗

Increased accuracy of multiphysics simulations through flexible execution, transient algorithms, and modular physics

The MOOSE framework is a foundational capability used by the NEAMS program to create over 15 different simulation tools for advanced nuclear reactors. Due to MOOSE’s broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. Such improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work described in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities were implemented in the same order as they are covered in this report: multiple time integrators in the same input file, initial design of framework Components, an input file Application block, extension of NetGen to 3D geometries in MOOSE, and deployment of executors in the multi-system paradigm. These five additions are fundamental capabilities that will be leveraged by many NEAMS applications.

97 MATHEMATICS AND COMPUTING↗

Conceptual Model of Autonomous Seed Germination Habitat for Mars Mission

As human space exploration extends to Mars, the ability to germinate seeds in extraterrestrial environments is becoming a necessity. Recent technological feats such as the development of the European Modular Cultivation System (EMCS) have made botany experiments possible on the International Space Station (ISS). Despite preliminary designs, a biocompatible plant life support system capable of traveling to Mars has yet to be developed. This study focuses on two preparatory measures regarding seed germination in spaceflight: analysis of seed dormancy protocols and compact autonomous habitat development.The objective of this project is to conceptualize a habitat capable of preserving arabidopsis plant seeds on a long duration spaceflight for the purpose of germinating the first plants on Mars. The proposed container will require a compact, low wattage system to provide gas ventilation, artificial light, and water. A visualization system will also need to be developed in order to monitor seed germination remotely. In order to test the effects of dormancy durations on plant viability, we will conduct a ground study to monitor seed germination in seeds which have been dormant for three, six, nine, and twelve months. We will also compare the effects of different sterilization procedures. The results of this study will be instrumental in developing a viable procedure for transferring the first living plants to Mars.

Peter, Jonah↗

Agent-based modeling for multimodal transportation of CO 2 for carbon capture, utilization, and storage: CCUS-agent

Here, to understand the system-level interactions between the entities in Carbon Capture, Utilization, and Storage (CCUS), an agent-based foundational modeling tool, CCUS-Agent, is developed for a large-scale study of transportation flows and infrastructure in the United States. Key features of the tool include (i) modular design, (ii) multiple transportation modes, (iii) capabilities for extension, and (iv) testing against various system components and networks of small and large sizes. Five matching algorithms for CO 2 supply agents (e.g., powerplants and industrial facilities) and demand agents (e.g., storage and utilization sites) are explored: Most Profitable First Year (MPFY), Most Profitable All Years (MPAY), Shortest Total Distance First Year (SDFY), Shortest Total Distance All Years (SDAY), and Shortest distance to long-haul transport All Years (ACAY). Before matching, the supply agent, demand agent, and route must be available, and the connection must be profitable. A profitable connection means the supply agent portion of revenue from the 45Q tax credit must cover the supply agent costs and all transportation costs, while the demand agent revenue portion must cover all demand agent costs. A case study employing over 5500 supply and demand agents and multimodal CCUS transportation infrastructure in the contiguous United States is conducted. The results suggest that it is possible to capture over 9 billion tonnes (GT) of CO 2 from 2025 to 2043, which will increase significantly to 22 GT if the capture costs are reduced by 40 %. The MPFY and SDFY algorithms capture more CO 2 earlier in the time horizon, while the MPAY and SDAY algorithms capture more later in the time horizon.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multi-Objective Optimization of a Bi-Metal High-Temperature Recuperator for Application in Concentrating Solar Power

Supercritical CO 2 closed Brayton cycles are a major candidate for future power cycle designs in concentrating solar power applications, with high-temperature recuperators playing an essential role in realizing their high thermal efficiency. Here, printed circuit heat exchangers (PCHEs) are often chosen for this role due to their thermal-hydraulic and mechanical performance at high temperatures and pressures, all while remaining compact. However, PCHEs can be costly because of the high-performance materials demanded in these applications, and the heat exchanger internal geometry is restricted by their manufacturing process. Additively manufactured heat exchangers can address both of these shortcomings. This work proposes a modular bi-metal high-temperature recuperator with integrated headers to be produced with additive manufacturing. Beginning with existing PCHE channel geometries, a 1D heat exchanger model is developed. Then, multi-objective optimization is used to maximize the heat transfer effectiveness of a lab-scale device while limiting its size. Two distinct channel geometries emerge from the optimization. Optimal designs achieve up to 88% effectiveness with negligible pressure drop. Deterioration of effectiveness due to axial conduction of heat in the heat exchanger walls is found to be a notable problem for lab-scale PCHEs, and the optimal designs obtained here minimize its detrimental effects. A sensitivity analysis reveals that the effectiveness of the recuperator is much less sensitive to variation in mass flowrate in off-design operation when axial conduction is significant, while increasing the length of the device easily increases effectiveness.

14 SOLAR ENERGY↗

Sensitivity of D meson azimuthal anisotropies to system size and nuclear structure

Recent experimental data at the Large Hadron Collider (LHC) confirmed that the soft sector azimuthal anisotropies in central XeXe collisions are sensitive to deformations in the wave function of the Xenon nucleus. Additionally, the CMS experiment found that D meson flow is slightly suppressed compared to other particle species when considering quark number scaling in small systems of pPb compared to PbPb. In this talk we used the D and B Mesons Modular (DAB-MOD) code coupled to Trento+v-USPhydro to calculate the R AA and v n ’s of D mesons using different energy loss models and Langevin techniques. Comparing D mesons R AA and v n in PbPb to XeXe collisions it is found that in central collisions D meson azimuthal anisotropies are sensitive to details in the nuclear structure wave function of Xenon. Additionally, we find that in mid-central collisions the smaller system size of XeXe suppresses D meson flow.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Equivariant K3 invariants

In this note, we describe a connection between the enumerative geometry of curves in K3 surfaces and the chiral ring of an auxiliary superconformal field theory. We consider the invariants calculated by Yau–Zaslow (capturing the Euler characters of the moduli spaces of D2-branes on curves of given genus), together with their refinements to carry additional quantum numbers by Katz–Klemm–Vafa (KKV), and Katz–Klemm–Pandharipande (KKP). We show that these invariants can be reproduced by studying the Ramond ground states of an auxiliary chiral superconformal field theory which has recently been observed to give rise to mock modular moonshine for a variety of sporadic simple groups that are subgroups of Conway’s group. We also study equivariant versions of these invariants. A K3 sigma model is specified by a choice of 4-plane in the K3 D-brane charge lattice. Symmetries of K3 sigma models are naturally identified with 4-plane preserving subgroups of the Conway group, according to the work of Gaberdiel–Hohenegger–Volpato, and one may consider corresponding equivariant refined K3 Gopakumar–Vafa invariants. The same symmetries naturally arise in the auxiliary CFT state space, affording a suggestive alternative view of the same computation. We comment on a lift of this story to the generating function of elliptic genera of symmetric products of K3 surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗