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NASA NTRSDate not supplied

Large Scale and Multi-Alloy Rocket Engine Component Development using Various Metal Additive Manufacturing Techniques

The NASA Marshall Space Flight Center (MSFC) has been involved with various forms of metallic additive manufacturing (AM) for use in liquid rocket engine component design, development, and testing since 2010. These AM techniques have been demonstrated to significantly reduce hardware cost, shorten fabrication schedules, increase reliability by reducing the number of joints, and improve hardware performance by allowing fabrication of designs not feasible by conventional means. The focus at the NASA MSFC for these metal additive manufacturing techniques include laser powder-bed fusion (L-PBF), blown powder directed energy deposition (DED), arc-based deposition, and Laser Wire Direct Closeout (LWDC). A variety of components have been evaluated and tested including thrust chamber injectors, injector components such as faceplates, regeneratively-cooled combustion chambers, regeneratively-cooled nozzles, gas generator and preburner hardware, and augmented spark igniters. To support these component applications in harsh environments, NASA has advanced a variety of “standard” additive manufacturing alloys such as those in the superalloy-family and also evolved new alloys including GRCop-84, GRCop-42, NASA HR-1, and JBK-75. The purpose of this presentation is to discuss the various component programs at the NASA MSFC using AM to develop, fabricate, and test combustion devices hardware and the evolution of the new additive alloys. One of these projects that will be highlighted is Rapid Analysis and Manufacturing Propulsion Technology (RAMPT), which includes new process development for large scale AM components, multi-metallic AM components, including unique component designs using additive manufacturing. Additional information will be provided on the development of other components, hot-fire testing, post-processing of AM techniques including surface enhancements (polishing) techniques, material and process characterization, future development programs, and dissemination of data to industry partners.

Additive Manufacturing↗

NASA NTRS2013

Robonaut 2 on the International Space Station: Status Update and Preparations for IVA Mobility

Robotics engineers, ground controllers and International Space Station (ISS) crew have been running successful experiments using Robonaut 2 (R2) on-board the ISS for more than a year. This humanoid upper body robot continues to expand its list of achievements and its capabilities to safely demonstrate maintenance and servicing tasks while working alongside human crewmembers. The next phase of the ISS R2 project will transition from a stationary Intra Vehicular Activity (IVA) upper body using a power/data umbilical, to an IVA mobile system with legs for repositioning, a battery backpack power supply, and wireless communications. These upgrades will enable the R2 team to evaluate hardware performance and to develop additional control algorithms and control verification techniques with R2 inside the ISS in preparation for the Extra Vehicular Activity (EVA) phase of R2 operations. As R2 becomes more capable in assisting with maintenance tasks, with minimal supervision, including repositioning itself to different work sites, the ISS crew will be burdened with fewer maintenance chores, leaving them more time to conduct other activities. R2's developers at the Johnson Space Center (JSC) are preparing the R2 IVA mobility hardware and software upgrades for delivery to the ISS in late 2013. This paper summarizes R2 ISS achievements to date, briefly describes the R2 IVA mobility upgrades, and discusses the R2 IVA mobility objectives and plans.

Ahlstrom, Thomas D.↗

NASA NTRS1997

Parallel supercomputing with commodity components

We have implemented a parallel computer architecture based entirely upon commodity personal computer components. Using 16 Intel Pentium Pro microprocessors and switched fast ethernet as a communication fabric, we have obtained sustained performance on scientific applications in excess of one Gigaflop. During one production astrophysics treecode simulation, we performed 1.2 x 10(sup 15) floating point operations (1.2 Petaflops) over a three week period, with one phase of that simulation running continuously for two weeks without interruption. We report on a variety of disk, memory and network benchmarks. We also present results from the NAS parallel benchmark suite, which indicate that this architecture is competitive with current commercial architectures. In addition, we describe some software written to support efficient message passing, as well as a Linux device driver interface to the Pentium hardware performance monitoring registers.

Performance↗

NASA NTRS2026

Raising TRL of Your Lunar Payload

Preparing payloads for the lunar surface requires rigorous testing that accurately captures the extreme environmental and operational conditions. This presentation provides an overview of the lunar relevant test capabilities at NASA JSC’s Astromaterials Research and Exploration Science (ARES) laboratories as well as the Energy System Test Area (ESTA) Lunar Development and Test Facility. These facilities allow teams to assess hardware performance in dusty vacuum environments, characterize interactions with high fidelity lunar regolith simulants, evaluate mechanical and thermal durability, and understand the effects of micrometeoroid and orbital debris impacts—critical factors for certifying payloads that will operate on the lunar surface or in orbit. While Lunar power challenges such as variable illumination, extreme temperatures, and dust driven degradation will be briefly summarized, the focus of this talk is on how JSC’s test infrastructure enables developers to validate designs, reduce mission risk, and ensure compatibility with CLPS and Artemis objectives. NASA JSC’s expertise and experience help industry, academic, and government teams prepare robust hardware ready for successful delivery and operation on the surface of the Moon.

Lunar Regolith Simulant↗

NASA NTRS2026

Raising TRL of Your Lunar Payload

Laboratories↗

NASA NTRS2018

Additive Manufacturing of Liquid Rocket Engine Combustion Devices: A Summary of Process Developments and Hot-Fire Testing Results

Additive Manufacturing (AM) of metals is a processing technology that has significantly matured over the last decade. For liquid propellant rocket engines, the advantages of AM for replacing conventional manufacturing of complicated and expensive metallic components and assemblies are very attractive. AM can significantly reduce hardware cost, shorten fabrication schedules, increase reliability by reducing the number of joints, and improve hardware performance by allowing fabrication of designs not feasible by conventional means. The NASA Marshall Space Flight Center (MSFC) has been involved with various forms of metallic additive manufacturing for use in liquid rocket engine component design, development, and testing since 2010. The AM technique most often used at the NASA MSFC has been powder-bed fusion or selective laser melting (SLM), although other techniques including laser directed energy deposition (DED), arc-based deposition, and laser-wire cladding techniques have also been used to develop several components. The purpose of this paper is to discuss the various internal programs at the NASA MSFC using AM to develop combustion devices hardware. To date at the NASA MSFC, combustion devices component hardware ranging in size from 100 lbf to 35,000 lbf have been designed and manufactured using SLM and deposition-based AM processes, and many of these pieces have been hot-fire tested. Combustion devices component hardware have included thrust chamber injectors, injector components such as faceplates, regeneratively-cooled combustion chambers, regeneratively-cooled nozzles, gas generator and preburner hardware, and augmented spark igniters. Ongoing and future developments for combustion devices have also included design of components sized for boost-class engines. Several design and hot-fire test iterations have been completed on these subscale and larger scale components, and a summary of these results will be presented as well.

Gradl, Paul↗

DOE OSTI2025

Solid State Transformer Architecture and Control Compensation for Common Mode Currents

A high-altitude electromagnetic pulse (HEMP) or similar geomagnetic disturbance (GMD) has the potential to impact the operation of large-scale electric power grids. By introducing low-frequency common-mode (CM) currents, these events can degrade the performance of critical system components, such as large power transformers by introducing CM currents which can lead to magnetic saturation of the transformer core. In this work, a solid-state transformer (SST) is developed to replace susceptible equipment and improve grid resiliency by safely absorbing these CM disturbances. This device will be referred to as a common-mode solid-state transformer (CM-SST). An SST architecture based on a four-legged AC/DC converter is developed. This architecture enables active control of CM signals without disturbing the AC voltages or the real and reactive power delivery capabilities. A system-level model of this architecture is created, and time-domain simulations are performed to evaluate the SST’s performance in response to simulated CM disturbances. A control strategy for mitigating CM current is also investigated. Hamiltonian surface shaping and power flow control (HSSPFC) is used to design a nonlinear controller for the SST’s output inverter. The objectives of the controller are to suppress CM-induced AC current offsets and regulate AC currents to desired setpoints. Nonlinear system analysis is applied to design and validate the controller. Two cases are tested: (a) the proposed four-leg inverter and (b) a standard three-leg inverter. The results show that the proposed controller rapidly mitigates CM disturbances while maintaining high-quality AC current waveforms in the four-leg configuration. Finally, the hardware performance of an SST prototype is evaluated. In particular, the ability of the SST to safely redirect and absorb CM currents is demonstrated, showing how it can protect neighboring conventional transformers in the system. The study confirms that appropriate control laws allow the SST to protect both itself and adjacent transformers during a HEMP or GMD event.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Surrogate Neural Architecture Codesign Package (SNAC-Pack)

Neural Architecture Search is a powerful approach for automating model design, but existing methods struggle to accurately optimize for real hardware performance, often relying on proxy metrics such as bit operations. We present Surrogate Neural Architecture Codesign Package (SNAC-Pack), an integrated framework that automates the discovery and optimization of neural networks focusing on FPGA deployment. SNAC-Pack combines Neural Architecture Codesign's multi-stage search capabilities with the Resource Utilization and Latency Estimator, enabling multi-objective optimization across accuracy, FPGA resource utilization, and latency without requiring time-intensive synthesis for each candidate model. We demonstrate SNAC-Pack on a high energy physics jet classification task, achieving 63.84% accuracy with resource estimation. When synthesized on a Xilinx Virtex UltraScale+ VU13P FPGA, the SNAC-Pack model matches baseline accuracy while maintaining comparable resource utilization to models optimized using traditional BOPs metrics. This work demonstrates the potential of hardware-aware neural architecture search for resource-constrained deployments and provides an open-source framework for automating the design of efficient FPGA-accelerated models.

Weitz, Jason [UC, San Diego] (ORCID:00090004631535↗

NASA NTRSDate not supplied

A Science-Focused Artificial Intelligence (AI) Responding in Real-Time to New Information: Capability Demonstration for Ocean World Missions

Introduction: Artificial intelligence (AI) has long been considered a potential mechanism to explore increasingly challenging environments, including those with extreme temperatures and pressures, limited communication capabilities, or those with demanding terrain. We posit that missions in extreme environments could deploy an onboard AI focused on science observations and goals in order to augment a traditional concept(s) of operations (ConOps). An onboard AI capability could perform functions such as data analysis in order to make high-level decisions, including prioritized data transmission for analysis by ground-based teams or autonomously-guided follow-on analyses that maximize science return. Such a capability would empower missions to respond to scientific data of interest in real-time; a mission could make observations and perform a preliminary analysis to alert ground-based scientists to an observation of interest, enabling an informed, rapid response from Earth-based teams. Enceladus Case Study for Onboard AI: We are developing an onboard AI capability for real-time telemetry response that formulates and carries-out informed decisions in service to established mission goals, enabling increased science return of a mission. We focus our AI development for use on a constellation of SmallSats orbiting Enceladus. Our Enceladus case study tests autonomous decision-making capabilities in scenarios with complex orbital dynamics, plume ejecta, extreme cold environments, power restrictions, and a requirement to maximize science return for a potential positive detection of life, while critically evaluating the potential for false positives. Telemetry includes simulated scientific data, spacecraft onboard operational data (e.g., position, velocity, and rotation), and engineering hardware performance data. Enceladus SmallSat Constellation. Our constellation includes eight SmallSat spacecraft in an 8:35 resonant orbit-based formation, leveraging Saturn’s gravitational forces to maintain stable orbits with global coverage around Enceladus. To our knowledge, we simulate the first stable configuration of multiple spacecraft in closed orbits around Enceladus, using a full ephemeris force model (Russell and Lara, 2009). Each spacecraft’s orbit will precess, causing an eastward ground track shift (from an orbiter’s perspective) of each spacecraft for each orbit. However, all spacecraft return to their original positions relative to Enceladus after eight Enceladus revolutions around Saturn. We model communication pathways between SmallSats to understand how information would need to be transmitted across the constellation to enable AI-driven decision-making and resource allocation across the fleet. Capability Demonstration. Our simulated capability demonstration inputs position, velocity, and rotation telemetry from our Enceladus-focused constellation simulations, and mass spectrometry data collected from abiotic and biotic laboratory-analog ocean world experiments (Theiling et al., 2018; Theiling, 2021; Da Poian et al., 2023). Data from these experiments are used to simulate MS measurements and different scenarios of science observations for onboard analysis performed on each of the eight spacecraft. For these demonstrations, we integrate 24 machine learning (ML) algorithms into an onboard intelligence as a ‘knowledge base’, including algorithms evaluating data quality and those predicting (with % confidence) gas composition, ocean aqueous chemistry, and whether the sample was influenced by microbial life. The onboard AI capability is designed to use the knowledge base to come to a consensus-based decision in the interpretation of the observed data in order to request additional action outside of a pre-defined ConOps. Requested actions could include e.g., prioritized downlink to Earth (for analysis by ground-based teams) or follow-on analyses performed across the constellation. The spacecraft’s intelligent onboard planner must then determine whether sufficient resources (e.g., time, power, etc.) are available and weigh the request with mission priorities. In our simulation, the constellation is able to identify potential biosignatures using onboard ML algorithms, evaluate the confidence of that prediction, and perform follow-on analyses across the fleet to confirm the detection, in order to best prepare a transmission of these data to Earth-based teams.

astrobiology↗

NASA NTRS2013

The Evolution of Software and Its Impact on Complex System Design in Robotic Spacecraft Embedded Systems

The growth in computer hardware performance, coupled with reduced energy requirements, has led to a rapid expansion of the resources available to software systems, driving them towards greater logical abstraction, flexibility, and complexity. This shift in focus from compacting functionality into a limited field towards developing layered, multi-state architectures in a grand field has both driven and been driven by the history of embedded processor design in the robotic spacecraft industry.The combinatorial growth of interprocess conditions is accompanied by benefits (concurrent development, situational autonomy, and evolution of goals) and drawbacks (late integration, non-deterministic interactions, and multifaceted anomalies) in achieving mission success, as illustrated by the case of the Mars Reconnaissance Orbiter. Approaches to optimizing the benefits while mitigating the drawbacks have taken the form of the formalization of requirements, modular design practices, extensive system simulation, and spacecraft data trend analysis. The growth of hardware capability and software complexity can be expected to continue, with future directions including stackable commodity subsystems, computer-generated algorithms, runtime reconfigurable processors, and greater autonomy.

software↗

NASA NTRS2010

Overview of Microbiological Tests Performed During the Design of the International Space Station Environmental Control and Life Support Systems

The design and manufacturing of the main Environmental Control and Life Support Systems (ECLSS) for the United States segments of the International Space Station (ISS) was an involved process that started in the late 1980's, with the assessment and testing of competing technologies that could be used to clean the air and recycle water. It culminated in 2009 with the delivery and successful activation of the Water Recovery System (WRS) water processor (WP). The ECLSS required the work of a team of engineers and scientist working together to develop systems that could clean and/or recycle human metabolic loads to maintain a clean atmosphere and provide the crew clean water. One of the main goals of the ECLSS is to minimize the time spent by the crew worrying about vital resources not available in the vacuum of space, which allows them to spend most of their time learning to live in a microgravity environment many miles from the comforts of Earth and working on science experiments. Microorganisms are a significant part of the human body as well as part of the environment that we live in. Therefore, the ISS ECLSS design had to take into account the effect microorganisms have on the quality of stored water and wastewater, as well as that of the air systems. Hardware performance issues impacted by the accumulation of biofilm and/or microbiologically influenced corrosion were also studied during the ECLSS development stages. Many of the tests that were performed had to take into account the unique aspects of a microgravity environment as well as the challenge of understanding how to design systems that could not be sterilized or maintained in a sterile state. This paper will summarize the work of several studies that were performed to assess the impacts and/or to minimize the effects of microorganisms in the design of a closed loop life support system.

Roman, Monsi C.↗

NASA NTRS2010

Microbiological Tests Performed During the Design of the International Space Station Environmental Control and Life Support Systems. Part 1, Bulk Phase: Bulk Phase - Part 1

The design and manufacturing of the main Environmental Control and Life Support Systems (ECLSS) for the United States segments of the International Space Station (ISS) was an involved process that started in the mid 1980s, with the assessment and testing of competing technologies that could be used to clean the air and recycle water. It culminated in 2009 with the delivery and successful activation of the Water Recovery System (WRS) water processor (WP). The ECLSS required the work of a team of engineers and scientist working together to develop systems that could clean and/or recycle human metabolic loads to maintain a clean atmosphere and provide the crew clean water. One of the main goals of the ECLSS is to minimize the time spent by the crew worrying about vital resources not available in the vacuum of space, which allows them to spend most of their time learning to live in a microgravity environment many miles from the comforts of Earth and working on science experiments. Microorganisms are a significant part of the human body as well as part of the environment that we live in. Therefore, the ISS ECLSS design had to take into account the effect microorganisms have on the quality of stored water and wastewater, as well as that of the air systems. Hardware performance issues impacted by the accumulation of biofilm and/or microbiologically influenced corrosion were also studied during the ECLSS development stages. Many of the tests that were performed had to take into account the unique aspects of a microgravity environment as well as the challenge of understanding how to design systems that could not be sterilized or maintained in a sterile state. This paper will summarize the work of several studies that were performed to assess the impacts and/or to minimize the effects of microorganisms in open, semi-closed and closed loop life support system. The biofilm and biodeterioration studies that were performed during the design and test periods will be presented in a future publication.

Roman, Monsi C.↗

NASA NTRS1999

Surface Tension Driven Convection Experiment-2 (STDCE-2)

Thermocapillary flows are known to become oscillatory (time-periodic), but how and when they become oscillatory in containers of unit-order aspect ratio are not yet fully understood. The present work is a part of our continuous effort to obtain a better understanding of the phenomenon. Thermocapillary flow experiments in normal gravity are limited to a narrow parametric range in order to minimize gravity and buoyancy effects, which is an important reason for our lack of full understanding of the oscillation phenomenon. One important unanswered question is what role, if any, free surface deformation plays in the oscillation mechanism. For that reason we performed thermocapillary flow experiments, called the Surface Tension Driven Convection Experiment-2 (STDCE-2), aboard the USML-2 Spacelab in 1995. The main objectives of the experiments were to investigate oscillatory thermocapillary flows in microgravity and to clarify the importance of free surface deformation in such flows. Steady and oscillatory thermocapillary flows were generated in cylindrical containers by employing two heating modes. A CO2 laser with adjustable power and beam diameter was used in the Constant Flux (CF) configuration to heat the free surface. The other configuration investigated in STDCE-2 was the Constant Temperature (CT) configuration in which a submerged cylindrical cartridge heater placed at the symmetry (axial) axis of the test container heated the fluid. Both heating modes cause non-uniform temperature distributions on the free surface, which generates thermocapillary flow. The flow field was investigated by flow visualization, and the temperature field was measured by thermistors and an infrared imager. The free surface shape and motion were measured by a Ronchi system. The hardware performed well and we were able to conduct more tests than originally planned. From the successful experiments a large amount of data was acquired. The analysis of the data is now nearly complete. Some important results are presented and discussed herein.

Masud, J.↗

NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗

DOE OSTI2022

A Roadmap for Edge Computing Enabled Automated Multidimensional Transmission Electron Microscopy

The advent of modern, high-speed electron detectors has made the collection of multidimensional hyperspectral transmission electron microscopy datasets, such as 4D-STEM, a routine. However, many microscopists find such experiments daunting since analysis, collection, long-term storage, and networking of such datasets remain challenging. Some common issues are their large and unwieldy size that often are several gigabytes, non-standardized data analysis routines, and a lack of clarity about the computing and network resources needed to utilize the electron microscope. The existing computing and networking bottlenecks introduce significant penalties in each step of these experiments, and thus, real-time analysis-driven automated experimentation for multidimensional TEM is challenging. One solution is to integrate microscopy with edge computing, where moderately powerful computational hardware performs the preliminary analysis before handing off the heavier computation to high-performance computing (HPC) systems. In this work, we trace the roots of computation in modern electron microscopy, demonstrate deep learning experiments running on an edge system, and discuss the networking requirements for tying together microscopes, edge computers, and HPC systems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

The construction of large-scale structure catalogs for the Dark Energy Spectroscopic Instrument

We present the technical details on how large-scale structure (LSS) catalogs are constructed from redshifts measured from spectra observed by the Dark Energy Spectroscopic Instrument (DESI). The LSS catalogs provide the information needed to determine the relative number density of DESI tracers as a function of redshift and celestial coordinates and, e.g., determine clustering statistics. We produce catalogs that are weighted subsamples of the observed data, each matched to a weighted `random' catalog that forms an unclustered sampling of the probability density that DESI could have observed those data at each location. Precise knowledge of the DESI observing history and associated hardware performance allows for a determination of the DESI footprint and the number of times DESI has covered it at sub-arcsecond level precision. This enables the completeness of any DESI sample to be modeled at this same resolution. The pipeline developed to create LSS catalogs has been designed to easily allow robustness tests and enable future improvements. We describe how it allows ongoing work improving the match between galaxy and random catalogs, such as including further information when assigning redshifts to randoms, accounting for fluctuations in target density, accounting for variation in the redshift success rate, and accommodating blinding schemes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Femtosecond MeV Electron Energy-Loss Spectroscopy

Pump-probe electron energy-loss spectroscopy (EELS) with femtosecond temporal resolution will be a transformative research tool for studying nonequilibrium chemistry and electronic dynamics of matter. Here in this article, we propose a concept of femtosecond EELS utilizing mega-electron-volt electron beams from a radio-frequency (rf) photocathode source. The high acceleration gradient and high beam energy of the rf gun are critical to the generation of 10-fs electron beams, which enables an improvement of the temporal resolution by more than 1 order of magnitude beyond the state of the art. In our proposal, the “referencebeam technique” relaxes the energy stability requirement of the rf power source by roughly 2 orders of magnitude. The requirements for the electron-beam quality, photocathode, spectrometer, and detector are also discussed. Supported by particle-tracking simulations, we demonstrate the feasibility of achieving subelectron- volt energy resolution and approximately 10-fs temporal resolution with existing or near-future hardware performance.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Detecting Hardware Trojans in PCBs Using Side Channel Loopbacks

Malicious modifications to printed circuit boards (PCBs) are known as hardware Trojans. These may arise when malafide third parties alter PCBs premanufacturing or postmanufacturing and are a concern in safety-critical applications, such as industrial control systems. In this research, we examine how data-driven detection can be utilized to detect such Trojans at run-time. We develop a flexible and reconfigurable PCB test bed derived from the popular open-source programmable logic controller (PLC) platform “OpenPLC.” We then develop a Trojan detection framework, which utilizes and analyzes multimodal side channels (e.g., timing, magnetic signals, power, and hardware performance counters). We consider defender-configurable input/output (I/O) loopback test, comparison with design-document baselines, and magnetometer-aided monitoring of system behavior under defender-chosen excitations. Our approach can extend to golden-free environments. Golden (known-good) versions of the PCBs are assumed not available, but design information, datasheets, and component-level data are available. We demonstrate the efficacy of our approach on a range of Trojans instantiated in the test bed.

42 ENGINEERING↗