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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Monte Carlo Simulation with CAD Interface for Calculation of 3D Maps of Residual Dose (CRADA)

Objective: To develop an easy-to-use software application to predict and mitigate radiation effects in research environment, space instruments, nuclear plants and medical facilities and help nonproliferation and national security efforts. Tech-X will develop standalone software libraries and command-line tools for ( 1) translating CAD into tessellated surfaces and tetrahedral meshes in GDML (for Geant4 and MARS 15), ROOT (for MARS 15) and HDF5 (for compact representation and for the visualization) formats, (2) healing CAD geometries to make them suitable for Monte Carlo simulations; (3) creating uniform and variable Cartesian and cylindrical meshes for detailed scoring; and ( 4) efficient Monte Carlo navigation in CAD geometries. JLAB will finish automation of simulations of residual dose in CAD geometries and integrate Tech-X software into Geant4 and MARS15. Finally, Tech-X will develop a Graphical User Interface to set up and heal CAD geometries, create input files, run and visualize simulations for residual dose. This application will run on local desktops, local and remote clusters and supercomputers and will be made available through public clouds, such as Amazon Web Services.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

DISARM: Target Electronic Device Informed Mitigation of Software Runtime Side-Channel Vulnerabilities

Program runtime/timing attacks exploit variations in a program’s execution times to extract sensitive information from the program (e.g. encryption keys, sensitive variable data, intellectual property). State-of-the-art solutions to runtime side-channel attacks attempt to balance the execution time of the sensitive code for different control flow paths to eliminate the timing leakage. However, during the mitigation process, most techniques do not consider the underlying hardware/device on which the target program is supposed to run on. This can lead to over-fixing (unnecessary extra operations), under-fixing (not solving the imbalance properly), and even failures. Here, we propose DISARM, a joint hardware-software methodology (unlike any existing solution) for mitigating runtime side-channel vulnerabilities that utilizes timing values from real embedded devices to generate targeted software fixes. We implement DISARM to support C/C++/Java source codes and validate it across 22 standard benchmarks. DISARM outperforms state-of-the-art solutions such as PENDULUM and DifFuzzaR in terms of execution time overhead, code size overhead, and correctness on five different embedded/edge devices.

Timing/runtime side-channel↗
DOE OSTI2024

StructuredFuzzer: Fuzzing Structured Text-Based Control Logic Applications

Rigorous testing methods are essential for ensuring the security and reliability of industrial controller software. Fuzzing, a technique that automatically discovers software bugs, has also proven effective in finding software vulnerabilities. Unsurprisingly, fuzzing has been applied to a wide range of platforms, including programmable logic controllers (PLCs). However, current approaches, such as coverage-guided evolutionary fuzzing implemented in the popular fuzzer American Fuzzy Lop Plus Plus (AFL++), are often inadequate for finding logical errors and bugs in PLC control logic applications. They primarily target generic programming languages like C/C++, Java, and Python, and do not consider the unique characteristics and behaviors of PLCs, which are often programmed using specialized programming languages like Structured Text (ST). Furthermore, these fuzzers are ill suited to deal with complex input structures encapsulated in ST, as they are not specifically designed to generate appropriate input sequences. This renders the application of traditional fuzzing techniques less efficient on these platforms. To address this issue, this paper presents a fuzzing framework designed explicitly for PLC software to discover logic bugs in applications written in ST specified by the IEC 61131-3 standard. The proposed framework incorporates a custom-tailored PLC runtime and a fuzzer designed for the purpose. We demonstrate its effectiveness by fuzzing a collection of ST programs that were crafted for evaluation purposes. We compare the performance against a popular fuzzer, namely, AFL++. The proposed fuzzing framework demonstrated its capabilities in our experiments, successfully detecting logic bugs in the tested PLC control logic applications written in ST. On average, it was at least 83 times faster than AFL++, and in certain cases, for example, it was more than 23,000 times faster.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

EnergyPlus Model Context Protocol Server (EnergyPlus-MCP) v0.1

EnergyPlus-MCP is the first open-source Model Context Protocol server specifically designed for EnergyPlus building energy simulation. This innovative software enables AI assistants and other applications to interact programmatically with EnergyPlus through a standardized, secure interface, eliminating traditional technical barriers in building energy modeling. The software provides specialized tools across five functional domains: server management, model configuration and loading, comprehensive building component inspection, systematic model modification, and simulation execution with results visualization. Key features include automated HVAC system discovery and topology mapping, advanced schedule analysis, intelligent model validation, and interactive visualization capabilities. EnergyPlus-MCP's layered architecture ensures robust separation between protocol communication and domain expertise, enabling scalable deployment across organizations, educational institutions, and research teams. Unlike direct LLM approaches that suffer from inconsistent results and security gaps, EnergyPlus-MCP provides validated, reliable interactions while maintaining scientific rigor. This democratizes sophisticated building energy analysis, making EnergyPlus accessible to broader audiences through conversational interfaces and streamlined workflows.

Li, Han [Lawrence Berkeley National Laboratory (LB↗
DOE OSTI2026

Cybersecurity at the Grid Edge: Protecting LA's Energy Systems in a Connected World

Join SoCalGas and the National Laboratory of the Rockies (NLR) for an insightful webinar on securing operational technology and energy systems. Los Angeles has the second-largest metro by population in the nation, making it vital to protect the energy infrastructure that powers day-to-day life. However, cybersecurity for energy systems is an immense challenge due to an increasing number of interconnected devices and stakeholders. While there was traditionally a limited need to secure energy infrastructure, the grid is only becoming smarter and more software-defined. Amid aging infrastructure and evolving cyber threats, the need to ensure the security of energy is at an all-time high. Together, SoCalGas and NLR are assessing the current state-of-the-art of the energy ecosystem to understand gaps in current best practices and technologies relevant to powering the city of Los Angeles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Accelerating Next-Generation Cybersecurity R&D Using AI Workflows: BADGER Project Development

The Broadband Automation for Distributed Grid Efficiency and Resilience (BADGER) project aligns with national strategic priorities for integrating emerging wireless technologies and advancing AI-driven security. As critical infrastructure modernizes toward increasingly software-defined and interconnected systems, the ability to leverage 5G/NextG networks and AI-enabled control becomes essential. This report outlines work at the National Laboratory of the Rockies (NLR) to develop a NextG-native security architecture powered by AI-RAN concepts and evaluate workflows that enable efficient and reliable architectures. Together, these efforts position the laboratory to accelerate innovation while directly supporting national security and resilience objectives.

5G/6G↗
DOE OSTI2024

ARCADE (Advanced Reactor Cyber Analysis and Development Environment)

SAND2025-11780O ARCADE (Advanced Reactor Cyber Analysis and Development Environment) software performs cybersecurity experiments on Defensive Cyber Security Architectures (DCSA) for Distributed Control Systems (DCSs). The application is integrated into a cohesive environment that performs cyber risk analyses and reduces costs. ARCADE can investigate the entire cyber-attack surface of a DCS from the physics of control, down to the firmware of individual components with automated efficiency. ARCADE has five major functional components: the Data Broker system, the virtualization environment, the cyber-attack simulator, the cyber-physical analysis system, and the physics simulator. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Valme, Romuald↗
DOE OSTI2026

Reassessment of PHDS Fulcrum40h High Purity Germanium (HPGe) Detector System Performance

This report presents a comprehensive evaluation of the updated PHDS Fulcrum40h High Purity Germanium (HPGe) detector system, benchmarking its performance, usability, and software capabilities against the current National Nuclear Security Administration (NNSA) Nuclear Emergency Support Team (NEST) HPGe Detector System Requirements Document. Systematic measurements were conducted using a single Fulcrum40h detector to assess key parameters including gamma efficiency and resolution, neutron detection efficiency, gamma pulse-pileup response, and gamma-to-neutron crosstalk. The Fulcrum40h system, acquired in August 2022, has undergone recent updates by PHDS to address deficiencies identified following the initial NEST requirements release. The results provide critical insights into the detector’s operational capabilities and compliance with NNSA NEST standards.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Sentinel

Network intrusion detection systems (NIDS) are commonplace in network security but they frequently employ algorithms that are computational demanding requiring hardware and software with significant power requirements. Two examples of such resource-intensive algorithms used for network security are regular expression matching and broader signature pattern matching which are commonly used in deep packet inspection (DPI). Network security algorithms that have large power requirements may be a challenge for low-power internet-of-things (IoT) environments, which generally lack the power resources to implement complex security measures like computationally expensive DPI at the edge. Furthermore, IoT environments incorporating 5G standalone networks have network latency constraints beyond just power that make DPI at the edge even more difficult. Programmable logic is ideally suited for machine learning inference for DPI because of its deep instruction level parallelism and single-cycle memory access. Machine learning approaches for DPI have been explored before using the programmable logic of field programmable gate arrays (FPGA) as a potential solution for NIDS approaches that would be power-suitable for IoT. However, those previous programmable logic NIDS approaches utilize either a supervised or unsupervised learning model. Sentinel utilizes the ensemble of these two machine learning approaches known as a semi-supervised approach which has shown promise in NIDS implementations. Sentinel provides a programmable logic implementation of a semi-supervised approach for DPI which operates at much lower power and latency than a GPU implementation with negligible loss of accuracy due to quantization through a logistic regressor.

Anderson, MatthewW [Idaho National Laboratory (INL↗
DOE OSTI2024

Integrating PCTRAN with AI-Driven Host-Intrusion Detection and Secured Container Systems for Advanced Malware Analysis (Summer Internship Report)

This study presents a solution for enhancing the security of the Personal Computer Transient Analyzer (PCTRAN) PC-based Nuclear Power Plant Simulator by integrating the software with an artificial intelligence (AI)-driven host-intrusion detection system (HIDS), in addition to a secured container system, for malware analysis. PCTRAN is a Windows XP-based software package that has the ability to simulate a variety of accident and transient conditions for nuclear power plants (NPPs). It offers a high-resolution replica of the Nuclear Steam Supply System (NSSS) and displays the status of important parameters allowing for operator interaction. By including AI-driven HIDS for the NSSS, the framework can identify security threats in real-time, ensuring the integrity of the nuclear simulation environment. Additionally, the secured container system offers the ability to isolate and analyze malware, preventing potential threats from affecting core systems. The integration process involves extensive testing and validation in order to ensure accuracy, reliability, and compliance with security policies. This framework sets a new precedent for secure simulation and training in NPP operations, and offers insight for future advancements in cybersecurity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Assessing Energy Infrastructure Devices for Vulnerabilities

Industrial control systems prove to be vital to the health and security of the nation in our critical infrastructure. Critical infrastructure includes the most foundational systems to support modern civilization which includes water and wastewater systems, communications, and the electricity we use to name a few sectors. However, these devices' overall composition remains largely unknown and are untested from a cyber security perspective. As part of the Cyber Testing for Resilient Industrial Control Systems (CyTRICS) program, I analyzed one such energy infrastructure device to better understand how it functions, what hardware and software components are present within it, and assess it for security vulnerabilities. To achieve this, I reverse engineered binary files using Ghidra to understand system functionality and learned more about how to collaborate with other researchers on a shared Ghidra project. I learned more about how web sockets function and how to interact with them through Python to test if they are secure or not. This work led me to assess possible vulnerabilities in this device and provide a better understanding of its composition and function, which are essential to INL's mission of securing our nation's energy infrastructure.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

PUFFIn Software Modeling for Quality Management

PUFFIn (PENELOPE User Friendly Fast Interface) was designed as a fast and simple Monte Carlo simulation tool for the transport of photons and electrons, with a primary purpose as a learning and education tool for a broad range of static configurations in the radiation processing industry. Development of the PUFFIn software is funded by the Office of Radiological Security (ORS) within the United States National Nuclear Security Administration (NNSA). PUFFIn helps fill the education and knowledge gaps in the industry, as identified in reports by Fermilab (2017) and the IAEA (2020). PUFFIn uses the PENELOPE (NEA-2023) physics engine to perform simulations on static configurations. PUFFIn has support for multiple geometry types from simple, single material simulations to full 3D configurations created from CAD input files or images from X-Ray Tomography scans. PUFFin was designed to be easy for the novice user, it will generate the input and geometry files required by PENLOPE and will display the output plots within the PUFFIn interface. PUFFin is distributed for free but requires a free workshop so users can be adequately trained in its use. Workshops have been presented in the past at Texas A&M university, the Aerial-CRT facility in Strasbourg France and Jakarta Indonesia. PUFFIn simulations have been validated by 10 MeV ebeam experiments done at Aerial-CRT in France (Radiation Physics and Chemistry 222 (2024) 111774). Further user experimental comparisons were made at the medical product hands on workshop at Texas A&M in October 2024.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

ByzSec — A Multi-layered Byzantine Resilient Architecture for Bulk Power System Protective Relays

Reliability, selectivity, and sensitivity are the fundamental attributes of any protection system, acting as the main drivers in the selection of schemes, and equipment. In high-voltage systems, microprocessor-based relays represent the industry’s preferred solution, providing engineers with a vast array of benefits. However, they remain vulnerable to cybersecurity events that may compromise their functionality. To help mitigate against potential cybersecurity risks, this paper presents a fault-tolerant, Byzantine Resilient (BR) architecture that significantly increases the cybersecurity attributes of a protection system while minimizing the amount of performance impacts and integration overheads introduced. The solution relies on an array of independent relays that utilize robust consensus methods (based on Spire [1], [2]) to ensure correct system behavior is achieved even when a relay has been compromised. Furthermore, the solution has been complemented with a custom-built Situational Awareness engine that can be used to detect and identify potential threats. The implemented solution has been developed in consultation with three hardware vendors and has been tested to comply with the performance requirements of a 345kV differential protection scheme (87T). The results indicate that the proposed architecture is a comprehensive solution that: supports the strict correctness and performance requirements of the bulk power grid while providing a cost-effective alternative that offers a seamless, long-term solution.

byzantine security, Fault Tolerant Application Sof↗
DOE OSTI2026

Firmware Tampering Detection in Heavy-Duty Vehicles through J1939 CAN Analysis

Modern heavy-duty vehicles rely on complex networks of Electronic Control Units (ECUs) that communicate using the J1939 protocol. While this system makes it easier to update and configure vehicle components, it also opens the door to serious cybersecurity risks if not properly secured. This work investigates the potential for firmware tampering through the J1939 communication protocol, which enables ECU configuration and reprogramming over the Controller Area Network (CAN) bus. By monitoring CAN traffic during legitimate maintenance operations and reverse-engineering OEM diagnostic software, we identified common and proprietary J1939 message identifiers, authentication patterns, and vulnerabilities within Unified Diagnostic Services (UDS). These findings demonstrate that inadequate authentication mechanisms can allow malicious actors to alter ECU firmware or disable safety functions, posing severe operational and safety risks. Our analysis contributes to the development of vehicle intrusion detection systems capable of recognizing abnormal reprogramming activity and future firmware fingerprinting methods to verify software integrity across ECUs. This work highlights the importance of standardizing secure firmware authentication across manufacturers to strengthen cyber resilience in heavy-duty vehicle systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

A Review of Software for Designing and Operating Quantum Networks

Quantum networks development is crucial to realizing a production-grade network that can support distributed sensing, secure communication, and utility-scale quantum computation. However, the transition from laboratory demonstration to deployable networks requires software implementations of architectures and protocols tailored to the unique constraints of quantum systems. This paper reviews the current state of software implementations for quantum networks, organized around a three-plane abstraction of infrastructure, logical, and control/service planes. We cover software for both designing quantum network protocols (e.g., SeQUeNCe, QuISP, and NetSquid) and operating testbeds, with a focus on essential control/service plane functions such as entanglement, topology, and resource management, in a proposed taxonomy. Our review highlights a persistent gap between theoretical architecture and protocol proposals and their realization in simulators or testbeds, particularly in dynamic topology and network management. We conclude by outlining open challenges and proposing a roadmap for developing scalable software architectures to enable hybrid, large-scale quantum networks.

Network Design↗
DOE OSTI2025

Towards Automatically Matching Security Advisories to CPEs: String Similarity-based Vendor Matching

When a vulnerability is reported by the National Vulnerability Database (NVD), affected products are listed in the structured Common Platform Enumeration (CPE) format. Unfortunately, if the vulnerability is in a software library (e.g., Log4j), it will not include CPEs for each product containing that library. In these cases, security operators need to manually read the vendor's or third-party security advisories to see if their product is affected. However, these advisories do not report affected products in a structured format, which prevents automated processing, This paper makes the first effort towards automatically constructing structured CPEs for the vulnerable products in a non-NVD security advisory from the unstructured data in the advisory. Since this is a very challenging problem, this paper specifically focuses on the initial but key step of matching the un-structured vendor names in security advisories to the structured vendor representations in the standard CPE format. We explore the feasibility of using string similarity to solve the problem. The basic idea is to compare a vendor name from the non-NVD advisory with each vendor in the official CPE dictionary. The CPE vendor with the highest similarity score to the advisory's vendor will be considered as the match. We first conduct an experimental, comparative study of multiple mainstream string similarity metrics for this matching problem. To improve the performance, we then design a new string similarity metric that is adapted from an existing metric by weighing different tokens in the advisory's vendor name differently.

McClanahan, Kylie↗