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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 793 records · Page 44

Imaging APO-BMI with Micro X-ray Computed Tomography (CT)

APO-BMI is a high-strength, high-temperature, and low-density foam comprised of 1,2-bis(2-aminophenylthio) ethane (APO-Link, formerly Apocure-601) and 4,4’-bismaleimidodiphenylmethane (BMI) that is used structural applications within the aerospace and weapons manufacturing sectors. APO-link is the diamine reagent used to synthesize BMI, a thermosetting resin. This resin can remain in a molten, flowing state for an extended period of time before crosslinking, allowing addition of glass or carbon microballoons to form its final structure. A portion of the current project was to observe the thermal effects on the structural integrity of the foam associated with exposure to an ion beam. Features within the foam were imaged using micro X-ray computed tomography (CT). The resulting imaging provided evidence that microballoon structure remained mostly intact at the points of failure, indicating that the failure of the material was occurring in the binder material.

36 MATERIALS SCIENCE↗

Mechanical Failure Risk Management for In-Service CSP Nitrate Hot Tanks

The hot thermal energy storage tanks in many operating (Gen2) concentrating solar power plants are designed to contain molten nitrate solar salt at 565 Degrees Celsius and are constructed from 347H stainless steel (SS). From previous work, it is known that 347H SS weldments are potentially susceptible to stress-relaxation cracking (SRC), particularly in the heat-affected zone above 540 Degrees Celsius when no post-weld heat-treatment (PWHT) is performed. However, residual stresses can be reduced when weldments receive PWHT, while at the same time a crack-resistant microstructure is being generated. The overarching goal of this project was to optimize cost-effective, thickness-dependent, localized PWHT procedures and to investigate for feasible non-destructive evaluation (NDE) at commercial scale for hot tanks in Gen2 CSP using 347H SS.

14 SOLAR ENERGY↗

Bayesian learning for rapid prediction of lithium-ion battery-cycling protocols

Advancing lithium-ion battery technology requires the optimization of cycling protocols. A new data-driven methodology is demonstrated for rapid, accurate prediction of the cycle life obtained by new cycling protocols using a single test lasting only 3 cycles, enabling rapid exploration of cycling protocol design spaces with orders of magnitude reduction in testing time. We achieve this by combining lifetime early prediction with a hierarchical Bayesian model (HBM) to rapidly predict performance distributions without the need for extensive repetitive testing. The methodology is applied to a comprehensive dataset of lithium-iron-phosphate/graphite comprising 29 different fast-charging protocols. HBM alone provides high protocol-lifetime prediction performance, with 6.5% of overall test average percent error, after cycling only one battery to failure. Here, by combining HBM with a battery lifetime prediction model, we achieve a test error of 8.8% using a single 3-cycle test. In addition, the generalizability of the HBM approach is demonstrated for lithium-manganese-cobalt-oxide/graphite cells.

25 ENERGY STORAGE↗

Thiol–ene Click Chemistry Incorporates Hydroxyl Functionality on Polycyclooctene to Tune Properties

Polyolefins compose the majority of plastic waste, but conventional mechanical recycling degrades their properties, thereby reducing their value. We report the functionalization of a model for dehydrogenated polyethylene, polycyclooctene (PCOE), with thiol–ene click chemistry to install pendant hydroxyl ethyl thioethers. Functionalization of PCOE using mercaptoethanol via thiol–ene click chemistry yielded functionalization between 1.4 and 22.9% based on ethylene monomeric units. Reactions were well-controlled by varying the reagent stoichiometry and reaction time. Crystallinity and melting temperature decreased, and glass transition temperature increased with greater functionalization. Contact angle measurements reveal an increase in surface polarity with functionalization. Here, comparisons with poly(ethylene-co-vinyl alcohol) (EVOH) show comparable surface polarity at similar levels of alcohol functionalization. At 12% functionalization, the ultimate shear stress (USS) of functionalized PCOE in an adhesive configuration is 4.10 ± 0.48 MPa, comparable to EVOH. At >12% functionalization, the failure mode changed from adhesive to mixed adhesive–cohesive, and the USS decreased.

36 MATERIALS SCIENCE↗

Destructive reverse bias pinning in perovskite/silicon tandem solar modules caused by perovskite hysteresis under dynamic shading

In this work, we demonstrate how perovskite hysteresis can result in permanent reductions in power output in perovskite/silicon tandem modules—including irreversible hotspot-induced damage—from only brief periods of shading. We show that reverse bias events in which a perovskite cell is biased above a threshold voltage—which in this work we find to be as low as –1.1 V—produces a temporary reduction in power output that is of sufficient magnitude to keep the cell pinned in reverse bias after the shading event ends. As a hysteretic phenomena, this crucial failure mode may be overlooked by static models of perovskite-based solar cells. Higher reverse bias voltages exacerbate the temporary reduction in short-circuit photocurrent, which is also sensitive to the level of illumination under reverse bias. Numerical device modelling demonstrates that this effect is consistent with our understanding of perovskite hysteresis as a consequence of mobile ion-electron coupling controlling rates of non-radiative recombination over time. Measurements of the dynamic response of single-junction perovskite cells are extrapolated to two-terminal and four-terminal perovskite/silicon tandem module modelling. We validate these models with measurements from an equivalent electronic circuit that represents a two-terminal perovskite–silicon tandem mini module. Two module-level solutions are discussed that address this issue, which includes increasing the number of bypass diodes and choosing better suited silicon bottom cells with higher shunter resistance in two-terminal tandem modules.

14 SOLAR ENERGY↗

Real-Time Observation of Nanoscale Kink Band Mediated Plasticity in Ion-Irradiated Graphite: An In Situ TEM Study

Graphite IG-110 is a synthetic polycrystalline material used as a neutron moderator in reactors. Graphite is inherently brittle and is known to exhibit a further increase in brittleness due to radiation damage at room temperature. To understand the irradiation effects on pre-existing defects and their overall influence on external load, micropillar compression tests were performed using in situ nanoindentation in the Transmission Electron Microscopy (TEM) for both pristine and ion-irradiated samples. While pristine specimens showed brittle and subsequent catastrophic failure, the 2.8 MeV Au2+ ion (fluence of 4.378 × 1014 cm−2) irradiated specimens sustained extensive plasticity at room temperature without failure. In situ TEM characterization showed nucleation of nanoscale kink band structures at numerous sites, where the localized plasticity appeared to close the defects and cracks while allowing large average strain. We propose that compressive mechanical stress due to dimensional change during ion irradiation transforms buckled basal layers in graphite into kink bands. The externally applied load during the micropillar tests proliferates the nucleation and motion of kink bands to accommodate the large plastic strain. The inherent non-uniformity of graphite microstructure promotes such strain localization, making kink bands the predominant mechanism behind unprecedented toughness in an otherwise brittle material.

36 MATERIALS SCIENCE↗

Mitigation of Motor Stalling and FIDVR via Energy Storage Systems with Temporal Logic Specifications

The fault-induced delayed voltage recovery (FIDVR) phenomenon has been very common from the distribution system through the transmission system. It causes a delay on recovering significantly depressed local voltage after the fault is cleared, and it can also lead to more widespread cascading system failures. Mitigating this event with current control approaches is challenging and becoming a crucial issue. Here, a model predictive control-based strategy employing signal temporal logic specifications is proposed to help mitigate FIDVR. To this end, it investigates and extends a dynamic performance model allowing analytic insights into the system-wide impact of motor stalling and FIDVR. The proposed controller provides richer descriptions of voltage specifications addressing both magnitude and time simultaneously. We consider different control specifications with reactive power support from energy storage systems to prevent the voltage during/after the fault from dropping too low, and reduce the delay time of voltage recovery. The simulation results conducted with the IEEE 57 bus test network validate the proposed method and demonstrate the effectiveness of the mitigation strategy on FIDVR.

25 ENERGY STORAGE↗

PMK 1000 cone-socket ventilator fittings force testing to ISO 5356-1:2015 Standard

This memo summarizes the results of verification tests on a cone-socket fitting to the ISO 5356-1:2015 standard, annexes B and F. The components were found to meet requirements holding 50N tensile force and more than 35 N-cm of torque for 10 seconds without separating at 35°C with a fresh socket. Humidity control was unavailable; consequently, humidity was significantly lower than the values in the ISO standard. Several repeat tests of the fitting with force, torque, and time excursions give us confidence that the fittings perform suitably to the ISO standard. Force overload tests suggest that the samples will disengage under tension at around 69 N, while torque overload tests under a force of 50 N will fail at 79 N-cm of torque. If repeated tests are performed on the same component, the socket can deform and lead to the connection failing the standard requirements. However, such failures only occur with repeated testing, and the gripping of such units can be modified so that they pass the standard. This observation demonstrates that socket gripping is responsible for those failures and would not be a problem in application.

42 ENGINEERING↗

An Approach to Dependence Assessment in Human Reliability Analysis: Application of Lag and Linger Effects

Dependence assessment refers to an approach used in human reliability analysis (HRA) to adjust a human error probability (HEP) for the following action by considering the impact of the preceding action. It has been known to significantly affect the overall results of probabilistic safety assessment (PSA). If the dependence assessment is not adequate, the result could be unconvincing for explaining the operator failures in the context of PSA. To date, several methods and some recent research have identified suggestions for treating dependence issues in HRA; however, these are still exclusively based on the intrinsic approach of the Technique for Human Error Rate Prediction (THERP), an HRA method. THERP inevitably has a challenge with the subjectivity of expert evaluation as well as the requirement for PSA and HRA expertise with resource-intensive and time-consuming processes. This paper suggests an approach to dependence assessment that could not only minimize the influence of expert judgment, but also saves time to perform the analysis with reasonable manpower. It modifies existing HRA methods with considering lag and linger effects to apply dependence effects for them. Based on a representative HRA method, i.e., Standardized Plant Analysis Risk - HRA (SPAR-H), guidance for how to apply lag and linger effects for the HRA method is suggested. Then, an investigation is carried out to compare quantification results of the revised HRA method with that of the original approach based on experimental data.

99 GENERAL AND MISCELLANEOUS↗

Human Factors for Advanced Reactors

Existing light water reactors in the U.S. are primarily large baseload electricity generating facilities. The concept of operations for these plants remains largely unchanged since the advent of commercial nuclear power—the main control room serves as the hub of plant activities and is staffed with multiple licensed operators who work in tandem under the shift supervisor, and staff such as field workers support the control room remotely. While newer plants have brought the advent of digital human-machine interfaces to replace earlier analog and mechanical instrumentation and controls, much of the control process remains unchanged and manual. It is simply a newer version of legacy concepts. Advanced reactors potentially bring considerable changes to the size, fuel type, automation, and staffing of nuclear power plants, necessitating a fundamental shift not just from analog to digital, but further from human to automation, from onsite to remote, from control to monitoring, and from many to few operators. Despite this multitude of parallel evolutions in reactor designs, many of the vendors developing the next generation of reactors represent smaller research and development enterprises. It is therefore not feasible to address all aspects of plant design at the same time. In particular, the competing design aspects of new reactors present a significant challenge to the development of robust and human factored systems at the plant. As vendors develop new reactor designs, much of the early focus is naturally on the fuel and reactor system technology. Looming behind these early advances is the daunting prospect of first-of-a-kind control concepts that have not yet been developed or validated. A failure to address the human element of reactor design early will lead to missed opportunities. The quickest development process is the replication of existing concepts of operations at legacy plants, even when such systems were long ago surpassed by better human-machine technologies outside the nuclear industry. Conversely, attempting to undertake novel concepts of operations late in the design life cycle of a plant could result in protracted development efforts and delays in licensing and deployment. This does not have to happen, and it is imperative that human factors be considered now, early in the design of new reactors.

99 GENERAL AND MISCELLANEOUS↗

Cumulant methods for electron-phonon problems. II. The self-consistent cumulant expansion

Here in this paper we present a self-consistent cumulant expansion (SC-CE) and investigate its accuracy for the one-dimensional Holstein model with and without phonon dispersion. We show that for finite lattice sizes, the numerical integration of the SC-CE equations becomes unstable at long times. This defect is partially ameliorated when studying systems in the thermodynamic limit, enabling the demonstration that the SC-CE corrects many deficits of the standard perturbative CE in the (nondispersive) Holstein model. The natural phonon damping that arises in the more realistic dispersed Holstein model renders the SC-CE stable, allowing for a complete assessment of the method. Here, we find that self-consistency dramatically corrects many of the failures found in the perturbative CE, but also introduces some unphysical features. Finally, we comment on the potential use of SC-CE as a tool for calculating Green's functions in generic many-body problems.

36 MATERIALS SCIENCE↗

Exploring the Performance Boundaries of a Small Reconfigurable Multi-Mission UAV through Multidisciplinary Analysis

The performance of a small reconfigurable unmanned aerial vehicle (UAV) is evaluated, combining a multidisciplinary approach in the computational analysis of additive manufactured structures, fluid dynamics, and experiments. Reconfigurable UAVs promise cost savings and efficiency, without sacrificing performance, while demonstrating versatility to fulfill different mission profiles. The use of computational fluid dynamics (CFD) in UAV design produces higher accuracy aerodynamic data, which is particularly important for complex aircraft concepts such as blended wing bodies. To address challenges relating to anisotropic materials, the Tsai–Wu failure criterion is applied to the structural analysis, using CFD solutions as load inputs. Aerodynamic performance results show the low-speed variant attains an endurance of 1 h, 48 min, whereas its high-speed counterpart is 29 min at a 66.7% higher cruise speed. Each variant serves different aspects of small UAS deployment, with low speed envisioned for high-endurance surveying, and high speed for long-range or time-critical missions such as delivery. The experimental and simulation results suggest room for design iteration, in wing area and geometry adjustments. Structural simulations demonstrated the need for airframe improvements to the low-speed configuration. This paper highlights the potential of reconfigurable UAVs to be useful across multiple industries, advocating for further research and design improvements.

42 ENGINEERING↗

Uncertainty Quantification Enabled by Automatic Differentiation for Hydrodynamic Simulation of Shock‐to‐Detonation Transition in High Explosives

Quantifying the effects of uncertainty in a reactive burn model on the run-to-detonation time in high explosives (HEs) provides a robust methodology for assessing the probability of an HE failing the IHE qualification standard. Moreover, uncertainty quantification helps evaluate whether the model calibration accurately represents data outside the calibration set. This study uses a specialized hydrodynamic simulation code for modeling detonation to determine the run-to-detonation time of the HE PBX 9502 for various impact velocities. To quickly approximate uncertainties in the model, a surrogate was constructed using a Taylor series expansion centered at the mean of the input parameters. To obtain the sensitivities required for constructing the Taylor series, HYP-percomplex Automatic Differentiation (HYPAD) was implemented. HYPAD is a methodology for infusing existing codes with automatic differentiation capabilities by augmenting variables with one or more imaginary units to compute step-size independent partial derivatives. These derivatives are accurate to machine precision with respect to the implemented numerical algorithm, meaning their accuracy reflects that of the underlying method (e.g., integration or discretization schemes). Using reduced order modeling techniques, the mean and standard deviation of the run-to-detonation time of a shock within PBX 9502 were computed for a number of initial impact velocities. A weighted least squares regression was then performed to obtain a best fit curve and prediction interval for the computed statistics. Historical data points from explosively driven wedge tests were utilized to validate the prediction interval, ensuring its reliability in predicting future outcomes. With this prediction interval and a known safety constraint curve, the most probable point of failure and the probability of failure for the HE PBX 9502 were determined.

97 MATHEMATICS AND COMPUTING↗

High-Temperature Linear Receiver Enabled by Multicomponent Aerogels

Concentrating solar thermal (CST) technology has significant potential mainly due to its dispatchability and low cost of storage. However, to compete with other sources, including utility-scale solar PV, its final cost (cents/kWh) still needs to be lowered. Cost reduction can be achieved by improving the system level efficiency of the CST plants through the deployment of advanced power cycles, which operate at high temperatures of ~700°C. However, optical, and thermal losses pose a major challenge to the efficiency of such CST systems. The overall aim of this project is to investigate and de-risk a linear solar receiver concept called an Aerogel Insulated Receiver (AIR) that generates high temperatures (up to 700°C) at a low solar concentration ratio (<100) and with a high collection efficiency (optical × receiver). Our prior work has demonstrated the thermal stability1 and optical and heat-insulating properties2,3 of transparent aerogel insulation at a one-inch scale. The focus of this work is on (1) co-optimization of the geometry of the aerogel tile and receiver enclosure to fit a standard parabolic collector (PTC), (2) scale-up of aerogels into 4-inch tiles while preserving key properties, (3) experimental measurement of receiver heat loss (W/m) in a >70-cm test stand and validation of anticipated receiver performance at high temperatures. Regarding (1), appropriate optical and thermal models for a parabolic trough receiver (PTR) are developed and validated. The geometry of the aerogels and the receiver enclosure are co-optimized to maximize the collection efficiency. The model predicts a 54% collection efficiency at 700°C for an AIR design based on flat aerogels. By combining the collection efficiency with the power block efficiency of supercritical CO 2 cycles, we predict >10% improvements in peak plant efficiency relative to existing line-focusing CST systems. The application of curved plasmonic aerogels is predicted to further increase the collection efficiency to 64%. Regarding (2), we demonstrate the successful development of 6-inch-long refractory aerogel tiles with optical, thermal, and stability characteristics consistent with our prior work. This scale-up requires a transition to a larger ALD station and modifying the ALD process variables such as exposure time and the number of precursor doses. Regarding (3), we design and develop an AIR test stand measuring 3 feet in length. Heat loss performance analysis is carried out using the test stand. The results indicate that aerogel insulation can significantly reduce receiver thermal losses at the high operating temperatures required for next-generation PTRs. The experimental results agree with the heat loss performance predicted by our receiver model. Lastly, we conducted preliminary failure mode and effects (FMEA) and techno-economic (TEA) analyses to identify failure mitigation strategies and commercial opportunities, respectively. Overall, this project identifies key opportunities and challenges in deploying aerogel insulating receivers in next-generation line-focusing CST technologies.

14 SOLAR ENERGY↗

Automated Inspection of Criticality Control Overpacks for Surplus Plutonium Disposition: Qualification Update – 25313

In an effort to reduce the amount of nuclear waste in South Carolina, the Department of Energy (DOE) tasked the Savannah River Site (SRS) with diluting and disposing of the amount of plutonium in the state. This process involves the movement and shipment of over 100,000 criticality control overpacks (CCOs) throughout the project lifespan, lending itself to the use of automation to reduce worker radiation exposure and more efficiently utilize human capital. Due to the large scope, this overarching process was broken down into several different “automation projects” to be developed. The first opportunity pursued was the receipt and inspection of empty CCO drums coming into SRS, identified as Automation Project 1 (AP1), and is the focus of this paper. AP1 was developed to unpack incoming CCOs and inspect them for unwanted foreign objects and any damage to the drum or its contents. This process is accomplished by the combination of an automated guided vehicle (AGV) that delivers CCOs to a robotic arm which uses a suite of custom tools to disassemble a CCO, inspect the inside and outside of the CCO and its inner criticality control container (CCC), reassemble the CCC and CCO, and apply a tamper indicating device (TID) to the inspected drum. In past years, the robotic work cell had been developed in a small-scale testing facility for proof-of-concept. This year, major improvements were made to the robotic work cell to perform the process, including integration into the final facility where CCOs will be inspected. Other technical improvements include the implementation of sensor feedback and safety relays into the control system to allow the state of the work cell to be better tracked, and additional development of the TID application process to complete the robotic inspection. Further enhancements were made to the robotic vision processes and robot pathing, as well as development on a computer vision inspection process to detect inspection criteria anomalies in CCOs. In addition to developmental improvements, the work cell underwent a six-month testing period to ensure the project requirements were met. Results of this testing period demonstrate the work cell’s capability to meet project throughput goals at an acceptable level, successfully document the status of each CCO inspected, and reduce the toll on technical operations’ human power by two thirds. At the time of this paper, the work cell is capable of autonomously handling up to eight CCOs with an AGV, delivering CCOs to and from the robot work cell, and having a robotic arm perform a full receipt and inspection procedure on each CCO. Moving forward, repeatability will be improved so that these CCOs can be run back-to-back seamlessly, as well as improving the system to handle more significant edge cases and failure modes.

Spivey, Nicholas↗

Multimorphic Materials: Spatially Tailoring Mechanical Properties via Selective Initiation of Interpenetrating Polymer Networks

Access to multimaterial polymers with spatially localized properties and robust interfaces is anticipated to enable new capabilities in soft robotics, such as smooth actuation for advanced medical and manufacturing technologies. Here, orthogonal initiation is used to create interpenetrating polymer networks (IPNs) with spatial control over morphology and mechanical properties. Base catalyzes the formation of a stiff and strong polyurethane, while blue LEDs initiate the formation of a soft and elastic polyacrylate. IPN morphology is controlled by when the LED is turned “on”, with large phase separation occurring for short time delays (≈1–2 min) and a mixed morphology for longer time delays (>5 min), which is supported by dynamic mechanical analysis, small angle X-ray scattering, and atomic force microscopy. Through tailoring morphology, tensile moduli and fracture toughness can be tuned across ≈1–2 orders of magnitude. Furthermore, a simple spring model is used to explain the observed mechanical behavior. Photopatterning produces “multimorphic” materials, where morphology is spatially localized with fine precision (<100 µm), while maintaining a uniform chemical composition throughout to mitigate interfacial failure. As a final demonstration, the fabrication of hinges represents a possible use case for multimorphic materials in soft robotics.

36 MATERIALS SCIENCE↗

Uncertainty-Aware and Explainable Human Error Detection in the Operation of Nuclear Power Plants

The timely and accurate identification of incidents, such as human factor error, is important to restore nuclear power plants (NPPs) to a stable state. However, the identification of abnormal operating conditions is difficult because of the existence of multiple scenarios. In addition, to implement mitigation actions rapidly after an incident occurs, operators must accurately identify an incident by monitoring the trends of many variables. The mental burden posed by this can increase human error and cause failure in identifying incidents. Failure to identify incidents directly results in erroneous mitigation measures, which are detrimental to NPPs. In this study, we leverage uncertainty-aware models to identify such errors and thereby increase the chances of mitigating them. We use the data collected from a physical test bed. The goal is to identify both certain and accurate models. For this, the two main aspects of focus in this study are explainable artificial intelligence (XAI) and uncertainty quantification (UQ). While XAI elucidates the decision pathway, UQ evaluates decision reliability. Their integration paints a comprehensive picture, signifying that understanding decisions and their confidence should be interlinked. Thus, in this study we leverage UQ measures (e.g. entropy and mutual information) along with Shapley additive explanations to gain insights into the features contributing to both accuracy and uncertainty in error identification. Furthermore, our results show that uncertainty-aware models combined with XAI tools can explain the artificial intelligence–prescribed decisions, with the potential of better explaining errors for the operators.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗