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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Synthesis Plugin for Auralization of Rotor Self Noise

This paper describes the development and architecture of a software plugin for the NASA Auralization Framework that synthesizes rotor modulating broadband self noise. A conceptual overview of the synthesis process is reviewed. The architecture description includes use of the plugin within a broader framework to auralize rotorcraft flyovers. Use of the plugin is demonstrated for a six-passenger quadrotor urban air mobility reference vehicle design using collective-pitch control.

Self Noise↗
NASA NTRSDate not supplied

A Synthesis Plugin for Auralization of Rotor Self Noise

This paper describes the development and architecture of a software plugin for the NASA Auralization Framework that synthesizes rotor modulating broadband self noise. A conceptual overview of the synthesis process is reviewed. The architecture description includes use of the plugin within a broader framework to auralize rotorcraft flyovers. Use of the plugin is demonstrated for a six-passenger quadrotor urban air mobility reference vehicle design using collective-pitch control.

Auralization↗
DOE OSTI2025

A Flang Plugin for Fortran Feature Characterization

As new compute systems are developed, there is still a need to compile and execute codes authored in Fortran on these leading edge systems. In order to achieve this, development of compilers that support the latest hardware is continuously under development. Though the specification of Fortran is extensive, it is helpful to compiler authors to be able to prioritize the development of key features in order to get certain codes deemed important, e.g., applications of interest to leadership computing facilities, executable on leading edge compute systems. Identifying key features though is largely done through querying software experts or users of the Fortran applications of interest, who then manually report what features are and are not present. This exercise can both time consuming and error prone. To automate this process, we present a compiler plugin to Flang, the Fortran frontend for LLVM. This plugin is a tool that operates on the parse tree representation generated by Flang and detects key features based on walking parse tree nodes that correspond to features of interest. We show the result of our tool on four applications, three of which were manually profiled by software experts. We show the discrepancies between our tool and the manual characterization of the three applications, as well as generate a characterization for an application not yet profiled. We intend to open-source our tool in order to invite the community to benefit from the tool and make contributions for other features.

Cabrera, Anthony [ORNL]↗
NASA NTRS2015

The NASA Auralization Framework and Plugin Architecture

NASA has a long history of investigating human response to aircraft flyover noise and in recent years has developed a capability to fully auralize the noise of aircraft during their design. This capability is particularly useful for unconventional designs with noise signatures significantly different from the current fleet. To that end, a flexible software architecture has been developed to facilitate rapid integration of new simulation techniques for noise source synthesis and propagation, and to foster collaboration amongst researchers through a common releasable code base. The NASA Auralization Framework (NAF) is a skeletal framework written in C++ with basic functionalities and a plugin architecture that allows users to mix and match NAF capabilities with their own methods through the development and use of dynamically linked libraries. This paper presents the NAF software architecture and discusses several advanced auralization techniques that have been implemented as plugins to the framework.

Aumann, Aric R.↗
NASA NTRS2023

Plugin for Integrated Exoskeleton Simulations (PIES)

Upper extremity offload is a new capability to be developed for the Active Response Gravity Offload System (ARGOS) at the Johnson Space Center. To address the need, the Actuated Real-time Control for ARGOS Negation of Gravitational Effects on the Limbs (ARC-ANGEL) system is being designed and developed by the HumanWorks team in the Flight Systems Branch (ER3). The Plugin for Integrated Exoskeleton Simulations (PIES) is a multibody modeling and analysis capability developed by the Digital Astronaut Simulation (DAS) team in the Simulation and Graphics Branch (ER7). The C++ plugin is used in the open source biomechanics software, OpenSim (Stanford University), and integrates human multibody modeling with system dynamic modeling. The latest ‘flavor’ is the ANGEL with Passive and Powered Line of force Evaluation (APPLE) PIES.

Kaitlin Lostroscio↗
DOE OSTI2025

Enhancing EnergyPlus capabilities to model dynamic building envelopes using python plugin

Nearly half of the energy consumption in the United States is related to buildings, resulting in an urgent need to develop innovative technologies to improve building energy efficiency. Dynamic building envelopes, comprising switchable insulation and thermal energy storage materials, have been proposed recently as a promising solution to reduce buildings' heating and cooling loads by thermally coupling the indoor environment with the ambient environment when beneficial while decoupling them when outdoor conditions are not favorable. Although various related technologies are still underway, the whole-building energy modeling tools, like EnergyPlus, do not have the capability to simulate the transient and dynamic nature of dynamic envelope materials and components to accurately predict their impact on building energy use. The objective of this study is to formulate a method in EnergyPlus simulation engine to model multilayer envelopes, comprising dynamic building materials with variable thermophysical properties, and discuss the changes made to the program using a Python plugin. Furthermore, the thermal performance of the dynamic envelopes using the proposed method is compared and verified with the results from a well-established commercial code, COMSOL Multiphysics. A parametric assessment is also conducted to evaluate the energy efficiency benefits of dynamic envelopes in a single-family residential building, demonstrating total annual energy savings up to 11.6 %, when a dynamic envelope operates alone, and up to 18.2 % when it is combined with a thin layer of phase change material as a thermal storage medium. Finally, a United States wide energy efficiency assessment is presented to showcase the geographical spread of the energy savings. The method designed and implemented in this study provides the researchers with the ability to implement their dynamic insulation methods in EnergyPlus and evaluate the whole building energy impact.

25 ENERGY STORAGE↗
DOE OSTI2024

AiiDA-INQ plugin

The AiiDA-INQ plugin will allow the INQ code developed at the lab to utilize the AiiDA workflow manager which enables high-throughput workflows. This includes provenance tracking, restart capabilities, job calculators, and other capabilities

Keilbart, NathanD↗
DOE OSTI2025

Binary Ninja Hcs08 Architecture Plugin

An architecture plugin for Binary Ninja to support the disassembly and decompilation of HCS08 software samples.

Larsen, Garrett [Idaho National Laboratory (INL), ↗
DOE OSTI2025

Binary Ninja Tricore Architecture Plugin

An architecture plugin for Binary Ninja to support the disassembly and decompilation of Tricore software samples.

Larsen, Garrett [Idaho National Laboratory (INL), ↗
DOE OSTI2025

Binary Ninja V850 Architecture Plugin

An architecture plugin for Binary Ninja to support the disassembly and decompilation of V850 software samples.

Larsen, Garrett [Idaho National Laboratory (INL), ↗
DOE OSTI2025

Binary Ninja Tic28x Architecture Plugin

An architecture plugin for Binary Ninja to support the disassembly and decompilation of TIC28X software samples.

Larsen, Garrett [Idaho National Laboratory (INL), ↗
DOE OSTI2024

Delta-Rice: A HDF5 Compression Plugin optimized for Digitized Detector Data

Delta-Rice is an HDF5 (The HDF Group et al., 2020) filter plugin that was developed to compress digitized detector signals recorded by the Nab experiment (Fry et al., 2019), a fundamental neutron physics experiment. This is a two-step process where incoming data is passed through a pre-processing filter and then compressed with Rice coding. A routine for determining the optimal pre-processing filter for a dataset is provided along with an example GPU deployment. When applied to data collected by the Nab data acquisition system, this method produced output files 29% their initial size, and was able to do so with an average read/write throughput in excess of 2 GB/s on a single CPU. Compared to the widely used Gzip compression routine, Delta-Rice reduces the file size by 33% more with over an order of magnitude increase in read/write throughput. Delta-Rice is available on CPU to users through the HDF5 library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Vulcan-Forge: Architecture and Design of a Multi-Modal Forensic Analysis Plugin for CALDERA

Forge and VULCAN together describe an open-architecture cybersecurity analysis ecosystem that unifies forensic artifact processing, detection engineering, and vulnerability intelligence within integrated platforms. Forge operates as a plugin for MITRE CALDERA, ingesting diverse evidence formats—including EVTX, PCAP/PCAPNG, CSV, JSON, YAML, XML, binaries, and archives—to construct a unified artifact graph enriched with severity scoring, TLP classification, and audit trails. It provides subsystems for artifact parsing, streaming structured-data visualization, NetworkMiner-based packet inspection, PE/.NET binary analysis, and LLM-assisted triage and rule generation, with outputs validated against CCCS-YARA and pySigma schemas. VULCAN complements this by serving as a cybersecurity analyst platform that integrates a Neo4j knowledge graph, Qdrant vector retrieval, SSVC-based triage, and a local LLM to deliver CVE intelligence and forensic analysis through a multi-source ingest pipeline drawing from NVD, CISA KEV, EPSS, MITRE ATT&CK, and CAPEC. Together, they bridge structured threat intelligence with automated forensic analysis and detection workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Integration of a grey-box refrigerated case model in EnergyPlus via Python plugin

Commercial buildings, in particular grocery stores (due mainly to their large refrigeration load), provide opportunities for energy cost reductions. Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity. This load flexibility could come from modifying the control of heating, ventilation, and air conditioning (HVAC) systems, refrigeration systems, or both. Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature, estimating load flexibility of refrigeration systems is nascent and has been a challenge, in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases. The existing refrigerated case model within EnergyPlus, a whole building energy simulation program, assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case. In addition, it does not encompass modeling of temperatures of the product inside the refrigerated case. This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential. In this paper, we present a grey-box model for modeling refrigerated cases in grocery stores, which include medium temperature and low temperature. Four cases are modeled; two are low-temperature closed cases and two are medium-temperature cases with one closed and one open. Data from an experimental facility are used to train and test the models. Results demonstrate the efficacy of the grey-box models in predicting the temperatures. This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment (case credits). These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost, develop and test unique algorithms that could affect refrigeration interactions with HVAC, and refine store design for any commercial building with refrigeration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗