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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Distributed Ada: Methodology, notation and tools

The task of creating software to run on a distributed system brings with it many problems not encountered in a uni-processor environment. The designer, in addition to creating a solution to meet the functional requirements of the applicaiton, must determine how to distribute that functionality in order to meet the nonfunctional requirements such as performance and fault tolerance. In the traditional approach to building distributed software systems, decisions of how to partition the software must be made early in the design process so that a separate program can be written for each of the processors in the system. This design paradigm is extremely vulnerable to changes in the target hardware environment, as well as being sensitive to poor initial guesses about what distribution of functionality will satisfy the nonfunctional requirements. The paradigm is also weak in that no compiler has a complete view of the system. Many of the advantages of using a powerful language system are lost in a one-program-per-processor environment. Another approach to the development of distributed software systems, Honeywell's Distributed Ada program, is presented.

Eisenhauer, Greg↗
NASA NTRS2019

Planetary Protection Technologies for Planetary Science Instruments, Spacecraft, and Missions: Report of the NASA Planetary Protection Technology Definition Team (PPTDT)

Planetary bodies like Mars, Europa, and Enceladus pose the question, "How to study them without contaminating them and destroying future prospects to detect life, if it is there?" The natural trade-off, of course, is that the cleaner your spacecraft, the more you can explore such a body without risk of contaminating it. As chartered by NASA Headquarters, the Planetary Protection Technology Definition Team (PPTDT) was asked to provide a report covering six different areas related to the engineering and technology challenges of implementing planetary protection requirements on solar system exploration missions, including: Assessment of technical and engineering challenges to applying available microbial-reduction methods, including recontamination prevention, to spacecraft hardware and instruments, to meet current NASA requirements on preventing the forward contamination of potentially habitable worlds by future spacecraft missions (orbiters, atmospheric missions, landers, penetrators, and drills); Identification of spacecraft and instrument materials known to be compatible with existing planetary protection protocols; Planetary protection protocols/processes available or which appear promising, and areas ripe for technological development; The technical and engineering challenges in ensuring that spacecraft hardware and instruments can meet organic cleanliness requirements needed to ensure high confidence in differentiating Earth contamination from extraterrestrial signals to avoid false negative as well as false positive results; Approaches for mitigating the identified challenges that would allow instruments to be flown successfully at the required levels of cleanliness and microbial reduction, beginning with identification of commonly used materials and spacecraft hardware that are compatible (or particularly vulnerable) to planetary protection protocols; Engineering, technology, and scientific research and development that could be funded by NASA to provide future capabilities to field scientific instruments and spacecraft on missions that require either subsystem or system-level microbial reduction and recontamination prevention.

John D. Rummel↗
NASA NTRS2018

Ground Software Technologies – Embracing Change: Mission Drivers and Technology Opportunities to Enable Long Lived Missions

Mission lifecycles have proven to extend well beyond their original design. The benefits to this are countless but introduce challenges in today’s rapidly changing ground infrastructure and software technologies used to enable mission success. What remains constant is the risk posture missions maintain when accepting change and the use of new technologies. Larger missions are ready for change in early lifecycle development but near launch and especially in operations, few continue to evolve beyond what is set in place in phase C. This paper will discuss how the Advance Multi-Mission Operations System (AMMOS) intends to address, three driving missions concerns: Maintaining functionality (hardware/software) for decades, rapidly responding to security vulnerabilities in software, and finally the ability to quickly evolve infrastructure and software changes. These driving concerns are briefly described below: 1. Maintaining functionality (hardware/software) for decades. Hardware updates considerably faster than 10 years ago. Expectations that a system can remain in place for more than 10 years is no longer valid. Expecting to find hardware replacements for a system older than 5 years will increasingly become more and more challenging. How than do missions plan for hardware changes for long lived missions? Principle Objective: Provide abstraction by virtualizing and containerizing software abstract away any hardware dependencies and package up the application lightweight units. 2. Rapidly responding to security vulnerabilities in software. Cost is often the main impediment and largely driven by the revalidation and testing of system that undergo change. In todays, environment security updates are a major diver demanding systems remain up to date. How then do missions accept these changes and avoid large testing efforts? Principle Objective: Help reduce the cost of re-testing by automation of testing, deployment, and compartmentalizing change. 3. Ability to quickly evolve infrastructure and software changes. Responding quickly to change is similar to the second concern in this paper regarding security vulnerabilities. In this case, it address broader concerns of updating software and infrastructure on a more realistic timeline. How do missions stay up to date with the most recent versions of software and allowing for improved functionality? Principle Objective: Use continuous integration techniques at the system level to ensure rapid turnaround. This paper explores each of these concerns in more detail. It focuses the AMMOS’s current plans, challenges and current roadmap.

Giovannoni, Brian J.↗
DOE OSTI2026

Evaluation of Hardware and Software Bill of Materials (HBOMs/SBOMs) Extraction Methods

Hardware and software bills of materials (HBOMs and SBOMs) provide important visibility into the components, dependencies, and supply chain relationships within programmable digital devices. This visibility is critical for advanced nuclear reactor applications, where use of common or shared hardware components, software libraries, suppliers, or manufacturing processes may create common cause failure (CCF) vulnerabilities despite apparent diversity. This paper evaluates current approaches for obtaining and analyzing HBOMs and SBOMs in support of CCF, diversity and defense-in-depth (D3) assessments, and begins to explore potential methods for artificial intelligence/machine learning-based analysis. The availability of BOM information from advanced reactor manufacturers and vendors, representative hardware and software categories found in advanced reactor systems continues to limit research [13]. This paper compares commonly used BOM formats, including CycloneDX, SPDX, and SWID. It also surveys publicly available tools for generating BOMs from source code, compiled binaries, and hardware-related information, noting limitations in language coverage, system age, and format interoperability. Finally, this paper evaluates methods for correlating BOM data with vulnerability and exploitability information, including VEX, CVE, and CWE resources. The findings indicate that publicly available nuclear-vendor BOMs are limited, making third-party extraction and research into novel analysis techniques necessary.

Cybersecurity↗
DOE OSTI2024

A full-scope, high-fidelity simulator-based hardware-in-the-loop testbed for comprehensive nuclear power plant cybersecurity research

Nuclear power plant (NPP) cybersecurity research often relies on hardware-in-the-loop (HIL) testbeds that integrate real hardware components into simulated environments. These testbeds allow researchers to identify vulnerabilities, evaluate attack impacts, and test security measures in a controlled setting. Furthermore, previous HIL testbeds lacked fidelity to accurately represent real nuclear systems, limiting the scope of cybersecurity analysis. This study presents the creation of a HIL testbed, devised upon a full-scope, high-fidelity NPP simulator, to facilitate realistic and comprehensive cybersecurity research. To demonstrate its capabilities, the control logic for the steam generator water level was migrated from the simulator to an external programmable logic controller. As a practical application of the developed testbed, supply chain attack scenarios were simulated by injecting malicious code into the controller logic, and the effects of manipulating sensor inputs and control commands were observed. While this HIL testbed provides more detailed simulations, enhanced realism, and wider applicability compared to other options utilizing a less complex simulator, it is also more intricate and costly. For this reason, we include a detailed comparison with some alternative architectures to aid fellow researchers and practitioners in the selection of a suitable HIL architecture based on specific research objectives.

47 OTHER INSTRUMENTATION↗
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 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

Assessment and Coordination of EVSE Cybersecurity Standards

Cybersecurity certification programs for Electric Vehicle Supply Equipment (EVSE) are fragmented due to no single certification covering all aspects of the device and additionally the existence of multiple programs and under different levels of regulation. These devices are also confronted by the intricate assembly of product software, firmware, and hardware. Devices contain both logical and physical interfaces. These multifaceted devices have vulnerabilities at many levels and interconnect with other potentially vulnerable systems including the electric vehicle, the cloud where data and payment information are stored, and the electric grid and electric grid equipment including utilities. Of the EVSE certification programs that are found, none are directly for the cybersecurity of EVSE. Many standards are for safety, specifically battery safety, some are cybersecurity standards for other types of equipment and can be modeled for EVSE. In specific, ISA/IEC 62443 is found to be significantly in line with EVSE security needs and will be used in future testing to certify EVSE and help guide the project to demonstrate where gaps exist, where strengths lie in the standard and how this can be used to lead the certification efforts in harmonizing EVSE cybersecurity standards. In addition, there are multiple efforts that are currently seeking to build EVSE standards or revise existing standards to address gaps. This effort is seeking to establish a cybersecurity program for EVSE that will inform customers and help increase the level of security across products and state EVSE procurements to achieve consistency across different jurisdictions.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1988

Management of human error by design

Design-induced errors and error prevention as well as the concept of lines of defense against human error are discussed. The concept of human error prevention, whose main focus has been on hardware, is extended to other features of the human-machine interface vulnerable to design-induced errors. In particular, it is pointed out that human factors and human error prevention should be part of the process of transport certification. Also, the concept of error tolerant systems is considered as a last line of defense against error.

Wiener, Earl↗
DOE OSTI2025

Computational Power of Random Quantum Circuits in Arbitrary Geometries

Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized classical simulations based on tensor network techniques, and their limitations shed light on the improvements to quantum hardware required to frustrate classical simulability. In particular, quantum computers having in excess of approximately 50 qubits are primarily vulnerable to classical simulation due to restrictions on their gate fidelity and their connectivity, the latter determining how many gates are required (and, therefore, how much infidelity is suffered) in generating highly entangled states. Here, we describe recent hardware upgrades to Quantinuum’s H2 quantum computer, enabling it to operate on up to 56 qubits with arbitrary connectivity and 99.843(5)% two-qubit gate fidelity. We define a class of circuits with random geometries that become hard to classically simulate in very low depth and implement them utilizing the flexible connectivity of H2. A careful analysis demonstrating the fast saturation of classical simulation complexity with depth indicates that H2 can yield data well beyond the reach of state-of-the art classical simulation methods at unprecedented fidelities. We find that the considerable difficulty of classically simulating H2 is likely limited only by qubit number, demonstrating the promise and scalability of the quantum charge-coupled device architecture as continued progress is made toward building larger machines. Published by the American Physical Society 2025

DeCross, M.↗
NASA NTRS2012

Development and Testing of Molecular Adsorber Coatings

The effect of on-orbit molecular contamination has the potential to degrade the performance of spaceflight hardware and diminish the lifetime of the spacecraft. For example, sensitive surfaces, such as optical surfaces, electronics, detectors, and thermal control surfaces, are vulnerable to the damaging effects of contamination from outgassed materials. The current solution to protect these surfaces is through the use of zeolite coated ceramic adsorber pucks. However, these pucks and its additional complex mounting hardware requirements result in several disadvantages, such as size, weight, and cost related concerns, that impact the spacecraft design and the integration and test schedule. As a result, a new innovative molecular adsorber coating was developed as a sprayable alternative to mitigate the risk of on-orbit molecular contamination. In this study, the formulation for molecular adsorber coatings was optimized using various binders, pigment treatment methods, binder to pigment ratios, thicknesses, and spray application techniques. The formulations that passed coating adhesion and vacuum thermal cycling tests were further tested for its adsorptive capacity. Accelerated molecular capacitance tests were performed in an innovatively designed multi-unit system containing idealized contaminant sources. This novel system significantly increased the productivity of the testing phase for the various formulations that were developed. Work performed during the development and testing phases has demonstrated successful application of molecular adsorber coatings onto metallic substrates, as well as, very promising results for the adhesion performance and the molecular capacitance of the coating. Continued testing will assist in the qualification of molecular adsorber coatings for use on future contamination sensitive spaceflight missions.

Abraham, Nithin↗
NASA NTRS1987

Fallible humans and vulnerable systems - Lessons learned from aviation

It is suggested that the problems being experienced in complex automatic systems are essentially due to the failure of information management and communication. The failure covers the entire spectrum: display devices and techniques, coding information so as to reduce human error, and information economy, i.e., resisting the temptation to bombard the operator with unlimited information simply because the system possesses the capability to do so. Since there has been great progress in hardware engineering, it is suggested that further attention is needed in the 'soft' side of systems. The approach should focus on (1) preventing human cognitive slips and (2) making the systems less vulnerable to such slips when they do occur. Most of the examples are taken from studies of cockpit automation.

Wiener, Earl L.↗
NASA NTRS2020

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system and the aviation industry has experienced a steady decrease in fatalities over the years. This can be attributed to both improved flight critical systems with redundant hardware and software protections, as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main approach for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave within the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety, creating labels for the data requires huge amount of effort and is largely impractical. To address this challenge, we developed a Convolutional Variational Auto-Encoder (CVAE), which is an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach as well as unsupervised clustering-based approach using KMeans++ and kernel-based approach using One-Class Support Vector Machine (OC-SVM) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Memarzadeh, Milad↗
NASA NTRSDate not supplied

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system. The industry has experienced a steady decrease in fatalities over the years. This can be contributed to both improved flight critical systems with redundant hardware and software protections as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main practice for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave with the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety creating labels for the data requires huge amount of efforts and is largely expensive. As a result, in this article, we develop a Convolutional Variational Auto-Encoder (CVAE), an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach (as an upper bound) as well as an supervised clustering based on K-Means (as a lower bound) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Milad Memarzadeh↗
DOE OSTI2024

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL

The clean energy transformation includes the integration of distributed energy resources with the power grid, which has led to a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Power grids infrastructure represents an operational technology environment that has become a system of systems, integrating heterogeneous devices which are both software-and hardware-intensive; as a result, there are increasing demands to exploit advances in the commodity of software-hardware infrastructures to improve energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, which leads to vulnerabilities and undesirable outcomes. The use of formal methods to characterize and prove system requirements removes ambiguity, increases automation, and provides high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system-level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗
DOE OSTI2025

SWARM: Reimagining scientific workflow management systems in a distributed world

Modern scientific workflows process massive amounts of data from diverse instruments and sensors, leveraging geographically distributed, heterogeneous compute and storage resources—from leadership-class systems to edge devices—connected by high-performance networks. The diversity of resources introduces challenges in harnessing their full potential, with resilience issues arising across applications, system software, networks, storage, and hardware. Today, workflow management systems (WMS) coordinate the execution of computation and data management tasks across target resources. However, WMS’s centralized nature makes them vulnerable to faults and scalability issues that may result in failures of entire computational campaigns. In conclusion, this paper introduces a novel agentic framework for workflow management, fully distributing and decentralizing the WMS functions and modeling them as swarm intelligence agents infused with advanced artificial intelligence solutions and traditional distributed computing algorithms that can make coordinated decisions in the presence of failures of the underlying cyberinfrastructure.

Swarm intelligence↗
DOE OSTI2025

SECURED: Simulator-Enhanced Control and Understanding of Reactor systems for cyber-Event Defense

The study discusses a learning approach for analyzing cyber-events in reactor systems using integrated hardware and personal computer simulator models. Key points include the rise in cyber-attacks and their sophistication in industrial control systems (ICS), the necessity for awareness, understanding, resource allocation, and preparation to combat these threats, and the digital transformation of old and new nuclear plants, increasing their exposure to cyber threats. It highlights the cyber vulnerabilities of advanced reactor systems, which rely on digital instrumentation and control for operations and safety functions, making them susceptible to cyber-attacks. The approach involves demonstrating reactor system plant ICS cyber-attacks under various operational conditions utilizing tools like simulator models and hardware-based kits. A strategic solution approach tailored to critical infrastructure is emphasized, along with community engagement for public and government support, adopting effective learning approaches, and the preparation for anticipated future challenges. The presentation concludes with a call to action to address challenges, leverage opportunities, and advance through lesson learning in cybersecurity for nuclear energy systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Advanced Research on Integrated Energy Systems Cyber Range

As digital technologies expand to meet the needs of a more autonomous, interconnected, and advanced power system, new cybersecurity complexities and vulnerabilities arise. The ARIES Cyber Range enables the energy sector to evaluate these evolutions and validate cybersecurity solutions without impacting live systems. Combining power grid-scale hardware with emulation and simulation approaches, the ARIES Cyber Range can faithfully replicate modern energy systems - from grid physics to communication networks, and everything in between - with real-world fidelity. At NLR, researchers and partners are answering complex power system cybersecurity questions, examining emerging threats to the electric sector, and de risking new security technologies, all at a mission-relevant speed that keeps pace with rapidly evolving systems and hazards.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗