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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 NTRS2000

Timing analysis by model checking

The safety of modern avionics relies on high integrity software that can be verified to meet hard real-time requirements. The limits of verification technology therefore determine acceptable engineering practice. To simplify verification problems, safety-critical systems are commonly implemented under the severe constraints of a cyclic executive, which make design an expensive trial-and-error process highly intolerant of change. Important advances in analysis techniques, such as rate monotonic analysis (RMA), have provided a theoretical and practical basis for easing these onerous restrictions. But RMA and its kindred have two limitations: they apply only to verifying the requirement of schedulability (that tasks meet their deadlines) and they cannot be applied to many common programming paradigms. We address both these limitations by applying model checking, a technique with successful industrial applications in hardware design. Model checking algorithms analyze finite state machines, either by explicit state enumeration or by symbolic manipulation. Since quantitative timing properties involve a potentially unbounded state variable (a clock), our first problem is to construct a finite approximation that is conservative for the properties being analyzed-if the approximation satisfies the properties of interest, so does the infinite model. To reduce the potential for state space explosion we must further optimize this finite model. Experiments with some simple optimizations have yielded a hundred-fold efficiency improvement over published techniques.

Naydich, Dimitri↗
NASA NTRS1991

Distributed-Computer System Optimizes SRB Joints

Initial calculations of redesign of joint on solid rocket booster (SRB) that failed during Space Shuttle tragedy showed redesign increased weight. Optimization techniques applied to determine whether weight could be reduced while keeping joint closed and limiting stresses. Analysis system developed by use of existing software coupling structural analysis with optimization computations. Software designed executable on network of computer workstations. Took advantage of parallelism offered by finite-difference technique of computing gradients to enable several workstations to contribute simultaneously to solution of problem. Key features, effective use of redundancies in hardware and flexible software, enabling optimization to proceed with minimal delay and decreased overall time to completion.

Rogers, James L., Jr.↗
NASA NTRSDate not supplied

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗
NASA NTRS1991

Assessment of probability of detection of delaminations in fiber-reinforced composites

Delamination is one of the critical defects in composite materials and structures. An ultrasonic C-scan imaging technique which maps out the acoustic impedance mismatched areas with respect to the sample coordinates, is particularly well suited for detecting and characterizing delaminations in composites. To properly interpret the results, it is necessary to correlate the indications with the detection limits and probability of detection (POD) of the ultrasonic C-scan imaging technique. The baseline information on the assessment of POD of delaminations in composite materials and structures is very beneficial to the evaluation of spacecraft materials. In this study, we review the principle of POD, describe the laboratory set-up and procedure, and present the experimental results as well as assessment of POD of delaminations in fiber reinforced composite panels using ultrasonic C-scan techniques.

Chern, E. J.↗
DOE OSTI2023

Probing individual single atom electrocatalyst sites by advanced analytical scanning transmission electron microscopy

Single atom electrocatalysts (SAEs) are promising next-generation materials for promoting a variety of important reactions, such as the oxygen reduction, nitrogen reduction, and CO 2 reduction reactions. While bulk characterization techniques such as X-ray absorption spectroscopy and Mössbauer spectroscopy have significantly enhanced our understanding of these catalysts, direct probing of individual single metal atom sites at the atomic scale is necessary to understand local variations in the properties of these sites and accelerate design and synthesis of improved SAEs. Aberration-corrected scanning transmission electron microscopy (STEM) has become a powerful tool for providing this type of atomic-scale information about SAE metal sites. These sites are typically unstable under the electron beam, however, which, in combination with conventional acquisition methods and detectors, has limited the type and quantity of information obtainable by spectroscopic STEM techniques. Here, we map multiple individual SAE metal sites in a nitrogen-doped carbon containing atomically dispersed Fe and Re (FeReNC) at the atomic scale by direct electron detection electron energy-loss spectroscopy (EELS). Direct electron detection provides an improved signal-to-noise ratio over conventional scintillator-based detectors and enables detection and real space localization of weak signals. In addition, we demonstrate an automated method for identification of metal atom positions, placement of the probe on these sites, and simultaneous EELS and energy dispersive X-ray spectroscopic (EDS) signal acquisition. This simultaneous acquisition of EELS and EDS provides access to the composition and bonding of a wide range of SAE metal sites. In this study, focusing the probe directly on the metal sites also increases the relevant data acquisition rate by more than an order of magnitude over two-dimensional mapping, enabling improved statistical measurements of site properties. The versatility, sensitivity, and speed that these techniques provide enhances our ability to probe the local elemental and chemical environment of a large number of individual SAE metal site structures at the atomic scale, enabling an improved understanding of the variations in the local properties of these electrocatalysts to be gained. As a result, significantly increased information about individual metal sites will be available to future electrochemical studies through these techniques, accelerating the development of advanced SAEs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

On the state estimation of structures with second order observers

The use of Linear Quadratic Regulator (LQR) control synthesis techniques implies the availability of full state feedback. For vibration control of structures, usually only a limited number of states are measured from which an observer model reconstructs the full state. It is shown that using second order observers is a viable technique for reconstructing the unmeasured states of structures under mildly restrictive conditions. Moreover, the computational advantages of the second order observer as compared to a first order observer indicate that significantly larger observer models may be utilized. Numerical examples are used to demonstrate the performance of second order observers. The implications of second order observers in the development of Controls-Structures Interaction (CSI) technology is discussed.

Belvin, W. Keith↗
DOE OSTI2020

On the mechanical behavior of a Nb 3 Sn superconducting coil during a quench: Two-dimensional finite element analysis of a quench heater protected magnet

New high-field accelerator magnets based on $Nb_3Sn$ superconductors are pushing the boundaries of magnet design and quench protection towards new limits. While their large stored energies and current densities result in a very challenging scenario for magnet protection, their great electromagnetic forces create also new requirements in terms of magnet design and stress management techniques. Furthermore, the strain sensitivity of $Nb_3Sn$ cables turns the electro-mechanical limits of the conductor into a parameter of the highest importance, where conductor degradation becomes a critical aspect in magnet operation. The coupling of all the above-mentioned considerations during quench is a case of special interest that adds further complexity to the design of $Nb_3Sn$ magnets. The objective of this paper is to provide a complete two-dimensional investigation of the coil and magnet structure mechanics during a quench event. Here, the analysis is performed using a combination of finite element codes that provide the necessary input for the mechanical study. The core of the modelling strategy relies on a thermal-electric model, whose results are directly used as loads in the mechanical simulation. In doing so, the stress evolution during and after a quench is obtained. We focus for this time in the analysis of a quench heater protected magnet, where dynamic effects are of less importance in contrast to other protection systems like CLIQ.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Constraining light thermal inelastic dark matter with NA64

A vector portal between the Standard Model and the dark sector is a predictive and compelling framework for thermal dark matter. Through co-annihilations, models of inelastic dark matter (iDM) and inelastic Dirac dark matter (i2DM) can reproduce the observed relic density in the MeV to GeV mass range without violating cosmological limits. In these scenarios, the vector mediator behaves like a semi-visible particle, evading traditional bounds on visible or invisible resonances, and uncovering new parameter space to explain the muon (g–2) anomaly. By means of a more inclusive signal definition at the NA64 experiment, we place new constraints on iDM and i2DM using a missing energy technique. With a recast-based analysis, we contextualize the NA64 exclusion limits in parameter space and estimate the reach of the newly collected and expected future NA64 data. Our results motivate the development of an optimized search program for semi-visible particles, in which fixed-target experiments like NA64 provide a powerful probe in the sub-GeV mass range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Filterscope Techniques for Parasitic Signal Screening

Here, the filterscope diagnostic uses bandpass filters and photomultiplier tubes (PMTs) to detect specific spectral emission lines. A filterscope was used to measure the W I 400.88 nm line emission as a function of ion energy on the Radio Frequency Plasma Interaction Experiment (RF PIE) for the purpose of assessing W erosion on plasma-facing components (PFCs). Different filter techniques are being explored and compared in order to effectively screen out nearby impurity lines, like the Ar II 401.39 nm line. The effectiveness of these techniques is determined by comparing the measurements to a high-resolution 1.0 m Czerny–Turner spectrometer with 0.012 nm spectral resolution. The ability to filter out nearby impurity emissions is useful when imaging PFCs in fusion devices including divertor and antenna guard limiters. Initial results with a helium plasma show little difference between the two techniques at higher bias voltages. In a helium plasma at lower dc bias voltages, a two-filter technique with filters at two separate wavelengths was shown to be more effective at screening out background signals. Data collected with an argon plasma however show the technique with overlapping filters on the line of interest is a closer match to spectrometer data at lower dc bias voltages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Additively Manufactured Strain Sensing for Nuclear Reactor Applications

Real-time monitoring of materials in harsh environments is a crucial technique towards reducing innovation time in nuclear systems. The successful measurement of real time, in-situ strain measurements during nuclear reactor operation requires innovative sensing solutions, including novel sensing strategies as well as advanced sensor design, manufacturing, and materials selection. In this paper, we will discuss two primary strategies for in-situ strain measurement strategies: additively manufactured (AM) capacitive strain gauges (CSGs) and digital image correlation (DIC). Current commercial strain gauges have limited applications in reactors due to the harsh operating conditions and non-trivial attachment strategies (i.e., welding, epoxy-adhesive) that can affect both the sensing performance and the underlying substrate under testing. AM CSGs are a viable solution as they have a low profile, low hysteresis, and wireless sensing integration capabilities that will enhance nuclear sensing technologies. In this work, the mechanical and thermal performance of the AM CSGs were tested up to 300 °C using ASTM standardized testing procedures to simulate the temperatures found in existing light water reactors. The AM CSGs had a similar performance across multiple samples which correlates to analytical models. This work leads towards the development of CSGs designed for higher temperatures and additional environmental factors found in Generation-IV reactors. Non-contact sensors, such as DIC, offer a less destructive way to measure deformation of materials when compared to alternative methods of in-situ strain determination, such as weldable strain gauges. However, DIC requires high contrast surfaces, which often relies on the implementation of artificial patterns. Using traditional splatter techniques to fabricate these patterns have limitations, including poor surface adhesion and reproducibility. In this work, AM fabrication techniques were implemented to avoid such limitations. Accordingly, aerosol jet printing (AJP) was used to print small scale periodic patterns of silver on stainless steel and aluminum tensile specimens. DIC was employed to monitor strain (up to 1100 µe) during temperature cycling from 23-600 °C. The results validated the use of AJP to better control pattern parameters for small fields of view applications at high temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Titanium Dioxide Nanomaterial Ink Production Through Laser Ablation Synthesis in Solution for Printed Electronics Applications

Flexible and printed electronics have become increasingly popular as they make possible the production of flexible, low-cost, multifunction devices that are unachievable through traditional manufacturing methods. The printed films are significantly impacted and thus limited by the existing ink production process. Herein, an alternate technique of generating high-quality titanium dioxide (TiO 2 ) nanoparticle ink compatible with aerosol jet printing using laser ablation synthesis in solution (LASiS) is showcased. Dynamic light scattering data and transmission electron microscopy confirm the particle size distribution. UV–vis measurements are performed, and the Beer–Lambert relationship is used to determine the concentration of the generated ink. The inks generated at two different repetition rates are compared: 200 kHz and 1 MHz. X-Ray diffraction analysis of the aerosol jet printed thin film post-thermal sintering confirms the grain size and phase purity of the printed thin films. This work demonstrates the effectiveness of the LASiS technique in producing printable nanoparticle inks with little-to-no postprocessing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Critical Review of Brazil Disk Techniques for Tensile Strength Characterization With an Emphasis on High Explosive Materials

Mechanical properties are a critical performance metric for many high explosive (HE) materials and tensile strength properties are particularly important. Direct tensile measurements using dogbone shaped samples are the gold standard but they have the disadvantage that they are fairly large and require samples machined from billets. Diametral compression, more commonly known as Brazil disk (BD) testing, is an indirect method for measuring tensile strength on smaller and more easily fabricated samples. A review of the BD literature is presented with an emphasis on tensile strength measurements in high explosive materials. BD literature is reviewed in three primary areas: (i) rocks and concrete, (ii) pharmaceutical materials, and (iii) high explosive materials. The literature for rocks/concrete is extensive and dates back over 80 years; despite this there is no consensus on the validity/accuracy of the BD technique or the optimal variant of the BD technique to employ. The pharmaceutical literature is the opposite, being limited in scope and quantity of studies. BD literature on high explosive materials falls in between, not as impressive as in the rocks/concrete community but more substantiative than in the pharmaceutical community. After the review of the literature practical parameters for HE BD testing and recommended future work is discussed.

Brazil disk↗
DOE OSTI2025

A universal inequality on the unitary 2D CFT partition function

We prove the conjecture proposed by Hartman, Keller and Stoica (HKS) [1]: the grand-canonical free energy of a unitary 2D CFT with a sparse spectrum below the scaling dimension $\frac{c}{12}$ + ϵ and below the twist $\frac{c}{12}$ is universal in the large c limit for all β L β R ≠ 4π 2 . The technique of the proof allows us to derive a one-parameter (with parameter α ∈ (0, 1]) family of universal inequalities on the unitary 2D CFT partition function with general central charge c ⩾ 0, using analytical modular bootstrap. We derive an iterative equation for the domain of validity of the inequality on the (β L , β R ) plane. The infinite iteration of this equation gives the boundary of maximal-validity domain, which depends on the parameter α in the inequality.

AdS-CFT Correspondence↗
DOE OSTI2024

Deep Generative Models in Energy System Applications: Review, Challenges, and Future Directions

In recent years, with the advent of mature machine learning products like ChatGPT, Stable Diffusion, and Sora, the world has witnessed tremendous changes driven by the rapid development of generative artificial intelligence (GAI). Beyond applications in text, speech, image, and video creation, deep generative models (DGMs) underpinning these cutting-edge technologies have also been employed by domain researchers to address scientific and engineering challenges. This paper aims to fill a gap in the research community by providing a systematic review of how DGMs have been utilized in energy system applications. After introducing four most popular DGMs, we review and categorize 196 research articles into five focus areas: data generation, forecasting, situational awareness, modeling, and optimal decision-making. Through this classification, we uncover trends in how DGMs are employed for each type of problem, highlighting GAI techniques that contribute to breakthroughs over traditional methods. We discuss limitations in existing literature, engineering challenges, and propose future directions, all tailored to the unique nature of problems in energy system engineering. Our goal is to offer insights for energy system domain researchers, providing a comprehensive view of existing studies and potential future opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of ceria-supported metal-oxide (MO x /CeO 2 ) catalysts via a one-pot chemical vapor deposition (OP-CVD) technique: Structure and reverse water gas shift reaction study

Current synthesis techniques for metal oxide (MO x )-supported catalysts have certain limitations of undesired target loading, ineffective dispersion of active species over the surface, uncontrolled particle size of active species, and complicated synthesis steps. Here, we developed a one-pot chemical vapor deposition (OP-CVD) methodology; by using which a solid metal precursor forms a vapor in a controlled condition and gets supported over the surrounding matrix. The theoretical stability followed by experimental validation using TGA is crucial for selecting the metal precursors. Three simple steps viz. premixing, dispersion, and rapid fixation by calcination are involved in the catalyst development via the OP-CVD approach. This study solely focused on the synthesis of 3d transition MO x over ceria support. The physicochemical characterizations of the prepared catalysts were performed by XRD, ICP-OES, SEM-EDX, CO pulse chemisorption, XANES, and EXAFS analyses to understand the crystal structure of involved species, target metal loading, dispersion, and particle size and prove the feasibility and viability of OP-CVD. The prepared catalysts were further tested for reverse water gas shift (RWGS) reaction to link their structural information with activity. The RWGS reaction data showed that the CO activity and CO selectivity were metal - and metal precursor-dependent. Higher CO activity of > 0.1 mol/h g-cat was observed for Cu and Co-based catalysts, with CO selectivity of ~100 %. This study provides an opportunity to produce efficient supported catalysts in a convenient way, providing effective catalytic activity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermodynamic modeling of adsorption at the liquid-solid interface

Adsorptive separation techniques are significantly energy efficient in comparison to conventional thermal separation techniques such as distillation. Despite extensive research and development activities undertaken for mixed-gas adsorption, the use of adsorption techniques for the separation of multicomponent liquid mixtures is still limited. A major barrier is the lack of accurate adsorption thermodynamic models, which form the scientific foundation of process simulation of such systems, making the translation to industrial scale challenging. In this work, we have rigorously computed the surface excess of adsorption for six binary liquid mixtures on silica gel at 303 K using the frameworks of the generalized Langmuir isotherm (gL) and the adsorbed solution theory (AST). The six binary liquid mixtures were formed by the pair-wise combinations of four components: benzene, 1,2-dichloroethane, cyclohexane, and n-heptane. We have based our calculations by considering simultaneous equilibria of three phases: saturated vapor phase, bulk liquid phase, and adsorbed phase. Further, the composition of the corresponding saturated vapor phase was estimated by the Nonrandom Two-Liquid activity coefficient model and experimental vapor-liquid equilibria data. The activity coefficients of the adsorbed phase, the central issue of multicomponent adsorption thermodynamics, were calculated using the adsorption Nonrandom Two-Liquid activity coefficient model. Devoid of simplifying assumptions, gL and AST provide rigorous thermodynamic frameworks for adsorption equilibria of multicomponent liquid mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Differential multi-probe thermal transport measurements of multi-walled carbon nanotubes grown by chemical vapor deposition

Carbon nanotubes (CNTs) are quasi-one dimensional nanostructures that display both high thermal conductivity for potential thermal management applications and intriguing low-dimensional phonon transport phenomena. In comparison to the advances made in the theoretical calculation of the lattice thermal conductivity of CNTs, thermal transport measurements of CNTs have been limited by either the poor temperature sensitivity of Raman thermometry technique or the presence of contact thermal resistance errors in sensitive two-probe resistance thermometry measurements. Here we report advances in a multi-probe measurement of the intrinsic thermal conductivity of individual multi-walled CNT samples that are transferred from the growth substrate onto the measurement device. The sample-thermometer thermal interface resistance is directly measured by this multi-probe method and used to model the temperature distribution along the contacted sample segment. The detailed temperature profile helps to eliminate the contact thermal resistance error in the obtained thermal conductivity of the suspended sample segment. A differential electro-thermal bridge measurement method is established to enhance the signal-to-noise ratio and reduce the measurement uncertainty by over 40%. The obtained thermal resistances of multiple suspended segments of the same MWCNT samples increase nearly linearly with increasing length, revealing diffusive phonon transport as a result of phonon-defect scattering in these MWCNT samples. The measured thermal conductivity increases with temperature and reaches up to 390 ± 20 W m –1 K –1 at room temperature for a 9-walled MWCNT. In conclusion, theoretical analysis of the measurement results suggests submicron phonon mean free paths due to extrinsic phonon scattering by extended defects such as grain boundaries. The obtained thermal conductivity is decreased by a factor of 3 upon electron beam damage and surface contamination of the CNT sample.

42 ENGINEERING↗