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At least 235 records · Page 13

Non-conformal attractor in boost-invariant plasmas

We study the dissipative evolution of (0+1)-dimensionally expanding media with Bjorken symmetry using the Boltzmann equation for massive particles in relaxation-time approximation. Breaking conformal symmetry by a mass induces a non-zero bulk viscous pressure in the medium. It is shown that even a small mass (in units of the local temperature) drastically modifies the well-known attractor for the shear Reynolds number previously observed in massless systems. For generic nonzero particle mass, neither the shear nor the bulk viscous pressure relax quickly to a non-equilibrium attractor; they approach the hydrodynamic limit only late, at small values of the inverse Reynolds numbers. Only the longitudinal pressure, which is a combination of thermal, shear and bulk viscous pressures, continues to show early approach to a far-off-equilibrium attractor, driven by the rapid longitudinal expansion at early times. Second-order dissipative hydrodynamics based on a gradient expansion around locally isotropic thermal equilibrium fails to reproduce this attractor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Lunar Sulfur Capture System

The Lunar Sulfur Capture System (LSCS) protects in situ resource utilization (ISRU) hardware from corrosion, and reduces contaminant levels in water condensed for electrolysis. The LSCS uses a lunar soil sorbent to trap over 98 percent of sulfur gases and about two-thirds of halide gases evolved during hydrogen reduction of lunar soils. LSCS soil sorbent is based on lunar minerals containing iron and calcium compounds that trap sulfur and halide gas contaminants in a fixed-bed reactor held at temperatures between 250 and 400 C, allowing moisture produced during reduction to pass through in vapor phase. Small amounts of Earth-based polishing sorbents consisting of zinc oxide and sodium aluminate are used to reduce contaminant concentrations to one ppm or less. The preferred LSCS configuration employs lunar soil beneficiation to boost concentrations of reactive sorbent minerals. Lunar soils contain sulfur in concentrations of about 0.1 percent, and halogen compounds including chlorine and fluorine in concentrations of about 0.01 percent. These contaminants are released as gases such as H2S, COS, CS2,HCl, and HF during thermal ISRU processing with hydrogen or other reducing gases. Removal of contaminant gases is required during ISRU processing to prevent hardware corrosion, electrolyzer damage, and catalyst poisoning. The use of Earth-supplied, single-use consumables to entirely remove contaminants at the levels existing in lunar soils would make many ISRU processes unattractive due to the large mass of consumables relative to the mass of oxygen produced. The LSCS concept of using a primary sorbent prepared from lunar soil was identified as a method by which the majority of contaminants could be removed from process gas streams, thereby substantially reducing the required mass of Earth-supplied consumables. The LSCS takes advantage of minerals containing iron and calcium compounds that are present in lunar soil to trap sulfur and halide gases in a fixedbed reactor downstream of an in-ISRU process such as hydrogen reduction. The lunar-soil-sorbent trap is held at a temperature significantly lower than the operating temperature of the hydrogen reduction or other ISRU process in order to maximize capture of contaminants, but is held at a high enough temperature to allow moisture to pass through without condensing. The lunar soil benefits from physical beneficiation to remove ultrafine particles (to reduce pressure drop through a fixed bed reactor) and to upgrade concentrations of iron and/or calcium compounds (to improve reactivity with gaseous contaminants).

Berggren, Mark↗

On the Physical Nature of Lyα Transmission Spikes in High-redshift Quasar Spectra

We investigate Lyman-alpha (Lyα) transmission spikes at 5.2 < z < 6.8 using synthetic quasar spectra from the “Cosmic Reionization on Computers” simulations. We focus on understanding the relationship between these spikes and the properties of the intergalactic medium (IGM). Disentangling the complex interplay between IGM physics and the influence of galaxies on the generation of these spikes presents a significant challenge. To address this, we employ Explainable Boosting machines, an interpretable machine learning algorithm, to quantify the relative impact of various IGM properties on the Lyα flux. Our findings reveal that gas density is the primary factor influencing absorption strength, followed by the intensity of background radiation and the temperature of the IGM. Ionizing radiation from local sources (i.e., galaxies) appears to have a minimal effect on Lyα flux. The simulations show that transmission spikes predominantly occur in regions of low gas density. Our results challenge recent observational studies suggesting the origin of these spikes in regions with enhanced radiation. We demonstrate that Lyα transmission spikes are largely a product of the large-scale structure, of which galaxies are biased tracers.

79 ASTRONOMY AND ASTROPHYSICS↗

The GA sulfur-iodine water-splitting process - A status report

The development of a sulfur-iodine thermal water splitting cycle is described. The process features a 50% thermal efficiency, plus all liquid and gas handling. Basic chemical investigations comprised the development of multitemperature and multistage sulfuric acid boost reactors, defining the phase behavior of the HI/I2/H2O/H3PO4 mixtures, and development of a decomposition process for hydrogen iodide in the liquid phase. Initial process engineering studies have led to a 47% efficiency, improvements of 2% projected, followed by coupling high-temperature solar concentrators to the splitting processes to reduce power requirements. Conceptual flowsheets developed from bench models are provided; materials investigations have concentrated on candidates which can withstand corrosive mixtures at temperatures up to 400 deg K, with Hastelloy C-276 exhibiting the best properties for containment and heat exchange to I2.

Besenbruch, G. E.↗

Impact of low reactivity fuel type on low load combustion, emissions, and cyclic variations of diesel-ignited dual fuel combustion

In this study, cyclic variations in dual fuel combustion with diesel ignition of three different low reactivity fuels (methane, propane, and gasoline) are examined under identical operating conditions. Experiments were performed on a single cylinder research engine (SCRE) at a low load of 3.3 bar brake mean effective pressure (BMEP). The start of injection (SOI) of diesel was varied from 280 to 330 absolute crank angle degrees (CAD). Engine speed, rail pressure, and boost pressure were held constant at 1500 rpm, 500 bar, and 1.5 bar, respectively. The energy substituted by the low reactivity fuel was fixed at 80% of the total energy input. It was found that diesel-methane (DM) and diesel-propane (DP) combustion were affected by diesel mixing to a greater extent than diesel-gasoline (DG) combustion due to the higher reactivity of gasoline. The magnitude of low temperature heat release was greatest for DG combustion followed by DM and DP combustion for all SOIs. The ignition delay for DG combustion was the shortest, followed by DM and DP combustion. DM and DP combustion exhibited more cyclic variations than DG combustion. Cyclic variations decreased for DM and DP combustion when SOI was advanced; however, DG combustion cyclic variations remained essentially constant for all SOIs. Earlier SOIs (280, 290, 300, and 310 CAD) for DM and (280, 290, and 300 CAD) for DP combustion indicated some prior-cycle effects on the combustion and IMEP (i.e. some level of determinism).

Engineering↗

Cathode Upcycling for Direct Recycling of Lithium‐Ion Batteries Using a Precipitation Approach

With the increased production of electric vehicles to reduce carbon emissions, the lithium-ion battery market to supply those vehicles has grown dramatically. To enhance battery sustainability and circularity, direct recycling methods aim to recover intact cathode materials. However, end-of-life cathode materials are typically 15–20 years old and often have lower energy density compared to current cathode materials. To address this challenge, a rapid precipitation process is developed to boost energy density by converting low Ni-compositions, LiNi 0.33 Co 0.33 Mn 0.33 O 2 (NMC111), into higher Ni-compositions (NMC622). This process forms a Ni-rich coating on cathode particles that diffuses into the core upon high-temperature relithiation, increasing compositional homogeneity. The upcycling process leverages existing infrastructure, offering low capital cost and minimal additional chemical input. Through ex situ tomographic transmission X-ray microscopy (TXM), 3D Ni:Co elemental mixing is quantified, confirming that elemental content evens at the secondary particle level with a mean NMC622 composition upon relithiation. However, elemental gradients remain in the single crystalline primary particles. Ex situ high-resolution and in situ wide-angle X-ray diffraction reveals concurrent structural changes during the relithiation process. These findings provide key insights into the structural and chemical mechanisms of elemental diffusion to obtain further improvements of increased capacity and retention through compositional conversion of cathode materials.

Cathode Upcycling↗

Hyperbolic exciton polaritons in a van der Waals magnet

Abstract Exciton polaritons are quasiparticles of photons coupled strongly to bound electron-hole pairs, manifesting as an anti-crossing light dispersion near an exciton resonance. Highly anisotropic semiconductors with opposite-signed permittivities along different crystal axes are predicted to host exotic modes inside the anti-crossing called hyperbolic exciton polaritons (HEPs), which confine light subdiffractionally with enhanced density of states. Here, we show observational evidence of steady-state HEPs in the van der Waals magnet chromium sulfide bromide (CrSBr) using a cryogenic near-infrared near-field microscope. At low temperatures, in the magnetically-ordered state, anisotropic exciton resonances sharpen, driving the permittivity negative along one crystal axis and enabling HEP propagation. We characterize HEP momentum and losses in CrSBr, also demonstrating coupling to excitonic sidebands and enhancement by magnetic order: which boosts exciton spectral weight via wavefunction delocalization. Our findings open new pathways to nanoscale manipulation of excitons and light, including routes to magnetic, nonlocal, and quantum polaritonics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multi-physics Topology OPtimization and Additive Manufacturing for High-temperature Heat Exchangers

This research significantly advances the understanding of high-temperature heat exchanger design through an integrated approach that combines topology optimization (TO), triply periodic minimal surface (TPMS) structures, additive manufacturing (AM) and thermohydraulic testing. Each of these components contributes uniquely to a unified, high-performance design, fabrication and testing workflow. Topology optimization serves as the foundation of the design methodology by providing a systematic way to determine the most effective material layout for separating hot and cold fluids while maximizing thermal performance. The researchers introduced a novel three-material optimization framework using two density fields to represent hot fluid, cold fluid, and solid domains. This approach enables automated discovery of optimal shapes and flow paths that cannot be intuitively designed, especially under constraints imposed by manufacturing technologies. Furthermore, constraints such as minimal wall thickness and overhang angles were embedded into the optimization process, ensuring that resulting designs are not only thermally efficient but also manufacturable using modern additive techniques. In parallel, the study delves into the use of Gyroid-based TPMS geometries for constructing the core of the heat exchanger. TPMS structures are known for their high surface area, excellent fluid mixing capabilities, and minimal pressure drop characteristics. The researchers applied a data-driven modeling framework using Heteroscedastic Sparse Gaussian Process Regression (HSGPR) combined with genetic algorithms. This allowed for the rapid evaluation and optimization of key geometric parameters such as frequency, iso-value, and phase shift. The result was a set of Gyroid structures tailored for high heat transfer and low flow resistance, demonstrating clear improvements over conventional straight-channel designs. After the designing process, additive manufacturing played a critical role by turning these highly complex, optimized geometries into physical components. Utilizing Laser Powder Bed Fusion (LPBF) with Haynes 282, the study demonstrated the feasibility of fabricating these heat exchangers at high precision. Post-processing methods, including dilation-erosion operations, were applied to ensure local features adhered to self-supporting constraints. The fabricated structures were then subjected to thermohydraulic testing under conditions representative of supercritical CO 2 Brayton cycles, validating the predicted performance and confirming the viability of the full design-to-fabrication pipeline. Finally, thermohydraulic testing across the above studies served as a crucial experimental validation of advanced heat exchanger. Under consistent high-temperature and high-pressure conditions using supercritical CO 2 , the testing demonstrated that both TO and Gyroid-based TPMS designs significantly outperformed conventional straight-channel HXs. The TO design achieved a 115% increase in UA and NTU and a 27.6% boost in gravimetric power density, while the data-driven optimized Gyroid design delivered a 166% increase in UA and NTU and improved effectiveness from 68.7% to 86.1%. These results validate the simulation models, confirm the manufacturability of complex geometries under AM constraints, and provide key insights into design-performance trade-offs, thereby advancing the development of high-efficiency, compact heat exchangers for extreme environments.

36 MATERIALS SCIENCE↗

Accelerated Simulation of Air Pollution Using NVIDIA RAPIDS

Atmospheric chemistry models are a central tool to study and forecast the impact of air pollution on the environment, vegetation, and human health. However, the numerical simulation of chemical kinetics is computationally expensive due to the stiffness of the system of ordinary differential equations that describes atmospheric chemistry. Here we present an alternative approach to the computation of atmospheric chemistry based on machine learning. Our training data set is produced using the NASA Goddard Earth Observing System (GEOS) model with GEOS-Chem chemistry, run on the NASA Center for Climate Simulation (NCCS) Discover supercomputing cluster on 384 Intel Xeon Haswell cores. This model spends more than 50% of total run time on solving atmospheric chemistry. The data set contains as input features the air pollution concentrations before solving the differential equations, together with some key physical parameters such as temperature and sun intensity. As target variables we define the air pollution concentrations after solving the differential equations. Using Dask-cuDF and Dask-XGBoost on the NVIDIA RAPIDS platform on 8 Tesla V100 GPUs, we generate from this training set gradient boosted decision tree models that can reproduce the simulation of chemical kinetics. We do this on the NCCS Advanced Data Analytics Platform (ADAPT) science cloud environment. Our application takes full advantage of recent advances in Dask-XGBoost, such as multi-node and multi-GPU scaling for distributed training with large data sets. The increase in training data size enabled by this is critical to capture the full range of chemical environments encountered across the globe and all annual seasons.The boosted tree models offer good predictability and show many of the features of the full chemistry reference simulation. Further improvements can be achieved through mass balance considerations and by accounting for error correlations. We incorporate the boosted tree models into the GEOS reference model using XGBoost's C API. This enables a seamless integration of the GPU trained models into GEOS-Chem, which is written in Fortran and optimized for use in a massively parallel CPU environment. We show the benefits of this approach and discuss the potential speedup of this machine learning accelerated atmospheric chemistry model.

Keller, Christoph A.↗

Boosting the Oxygen Reduction Performance via Tuning the Synergy between Metal Core and Oxide Shell of Metal−Organic Frameworks‐Derived Co@CoO x

Abstract Co core@Co oxide shell (Co@CoO x ) catalysts represent a large family with promising oxygen reduction reaction (ORR) catalytic activity. However, inadequate understanding of Co@CoO x synergy prohibits further pursuit of catalytic performance enhancement. Herein, a Co zeolitic−imidazolate framework was converted into metallic Co, followed by controlled air treatment to form Co@CoO x . The composition and structure evolution as a function of air treatment temperature were studied thoroughly through conventional and synchrotron (both ex‐situ and in‐situ) characterizations, confirming the coexistence of CoO and Co 3 O 4 in the shell. The optimal catalyst showed an ORR half‐wave potential of 0.87 V (vs. RHE) in an alkaline half‐cell and delivered high discharge capacity in an aprotic Li−O 2 battery (7,124 mAh g Cat+C −1 ) and an aqueous Zn−air battery (694 mAh g Zn −1 ) with good performance retention after durability test. Modeling simulation and density functional theory calculation confirmed the charge donation from metal core to oxide shell and shed light on new insights of how metal@metal oxide synergy impacted the ORR via tuning the charge conductivity, oxygen affinity and intermediate transfer pathway. This work opens up a venue to boost ORR catalytic activity from an interfacial synergy perspective.

Wang, Hao↗

Dataset for "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantification" Willard et al. (2025).

This data release provides all data and code used in the paper " "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantifications" Willard et al. (2025)" to model stream temperature, evaluate, and assess results. The associated manuscript explores the effect of different ensemble construction techniques across different common machine learning (ML) architectures for predictions in unmonitored basins. Modeling was done using long short-term memory (LSTM), gated recurrent unit (GRU), temporal convolution network (TCN), and extreme gradient boosting (XGBoost) models, and stream site coverage spans 1362 locations across the conterminous United States. The ensemble construction techniques investigated include ensemble by random weight initialization, differing hyperparameters, different random subsets of training data, different subselections of input features, different architectures, and Monte Carlo Dropout. The data is organized into these items items:Code repository and data for the paper " "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantifications" Willard et al. (2025).Code: stream_temp_ml_regionalization.zip contains the code repositoryData to run the code:- data_dir.zip -- contains all files that should be moved to the "DATA_DIR" variable defined in the "set_env_vars.sh" script in the code repository- metadata_dir.zip -- contains all files that should be moved to the "METADATA_DIR" variable defined in the "set_env_vars.sh" script in the code repositoryData produced by the code and used in the paper:- outputs_dir.zip - contains model output and results (outputs_dir/results), model weights (outputs_dir/models), and all other outputs used for the paper including feature importances.To cite this code, please use the following BibTeX or MLA entries:bibtex:@misc{willard2025streamensembles,author = {Jared Willard and Charuleka Varadharajan},title = {Dataset for "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantification"},year = {2024},doi = {10.15485/2527393},publisher = {ESS-DIVE Repository},url = {https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2527393}}MLA: Willard, Jared, et al. Dataset for "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantification". 2025. ESS-DIVE Repository, doi:10.15485/2448016.

54 ENVIRONMENTAL SCIENCES↗

A variational method for the sheath potential of hypersonic leading edges with space-charge limitations

Electron transpiration cooling for the leading edges (LE) of hypersonic aircraft utilizes thermionic emission; however, space-charge effects limit the electron emission rate, potentially diminishing the efficiency of this cooling mechanism. We develop a variational weak form of the Poisson equation that describes the sheath potential and then numerically solve it using the finite element method. This formulation has two main benefits: (1) the space-charge limit condition can be incorporated as a constraint and (2) it allows for the analysis of three-dimensional geometries with complex boundary conditions. We demonstrate that the current emitted from the surface of an LE is generally a small fraction of the Child–Langmuir limit due to space charge. We then propose several methods to enhance the emitted current from the surface and to boost the cooling effect of thermionic emission. These include increasing the plasma density, applying a negative surface potential, and using fringe fields under suitable geometric conditions. For a LaB6 emitting LE, the total emitted current is shown to be minimal and independent of the temperature of a surface with floating potential. However, when a negative potential is applied and the surface is heated, the emitted current follows the Richardson–Dushman relationship up to a critical temperature, beyond which it remains constant. At an applied surface potential of −5 V, the critical temperature is around 1700 K.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High/variable mixture ratio oxygen/hydrogen engines

A LOX/LH2 high/variable mixture ratio booster upper stage is described. The engine has high thrust-weight ratio as a booster and high specific impulse as an upper stage engine. Operation at high mixture ratio utilizes the propellants at high bulk density. The engine may use multiple turbopump-preburners for higher thrust ratings. The engine uses the full flow cycle to obtain minimum turbine inlet temperatures for a given chamber pressure and to avoid interpropellant shaft seals and other single point failure modes. A portion of the liquid hydrogen is used to regeneratively cool the thrust chamber assembly. The warmed hydrogen coolant is then used to drive the fuel boost turbopump. All propellants arrive at the gas-gas injector ready to burn. Shear mixing of the parallel flowing high velocity, low density fuel-rich gases with the high density, low velocity oxidizer-rich gases provides complete combustion with a modest chamber volume. Combustion stability is assured by the injection of the heated fuel-rich gases and the comparatively low volume ratio of the propellants before and after combustion. The high area ratio nozzle skirt is fitted with a low area ratio nozzle skirt insert for optimum low altitude performance. The overall engine characteristics make it a candidate for ALS, Shuttle-C, LRB, and SSTO applications.

Knuth, William H.↗

Water-Based Coating Simplifies Circuit Board Manufacturing

The Structures and Materials Division at Glenn Research Center is devoted to developing advanced, high-temperature materials and processes for future aerospace propulsion and power generation systems. The Polymers Branch falls under this division, and it is involved in the development of high-performance materials, including polymers for high-temperature polymer matrix composites; nanocomposites for both high- and low-temperature applications; durable aerogels; purification and functionalization of carbon nanotubes and their use in composites; computational modeling of materials and biological systems and processes; and developing polymer-derived molecular sensors. Essentially, this branch creates high-performance materials to reduce the weight and boost performance of components for space missions and aircraft engine components. Under the leadership of chemical engineer, Dr. Michael Meador, the Polymers Branch boasts world-class laboratories, composite manufacturing facilities, testing stations, and some of the best scientists in the field.

Source record↗

Anharmonic Cation–Anion Coupling Dynamics Assisted Lithium‐Ion Diffusion in Sulfide Solid Electrolytes

Abstract Sulfide‐based lithium superionic conductors often show higher Li‐ion conductivity than other types of electrolyte materials. This work unveils a unique Li‐ion conductive behavior in these materials through the perspective of anharmonic coupling assisted Li‐ion diffusion. Li hopping events can happen simultaneously with various types of lattice dynamics, while only a statistically important synchronization of motions may indicate coupling. This method enables a direct evaluation of the coupling strength between these motions, which more fundamentally decides if a specific type of lattice motion is really anharmonically coupled to the Li hopping event and whether the coupling can facilitate the Li diffusion. By a new ab initio computational approach, this work unveils a unique phenomenon in prototype sulfide electrolytes in comparison with typical halide ones, that Li‐ion conduction can be boosted by the anharmonic coupling of low‐frequency Li phonon modes with high‐frequency anion stretching or flexing phonon modes, rather than the low‐frequency rotational modes. The coupling pushes Li ions toward the diffusion channels for reduced diffusion barriers. The result from the lower temperature range (≈0–300 K) of simulation can also be more relevant to the application of solid‐state batteries.

Chemistry↗

Advanced Thin Film Core Technology: CIGS Final Technical Report (FTR)

Cu(In,Ga)Se 2 (CIGS) thin-film photovoltaics are a high-efficiency and reliable technology. This project completed research in two important areas and was designed to work collaboratively with industrial partners. Task 1: Alkali Science focused on alkali post-deposition treatments (PDT). PDTs have been instrumental in the dramatic voltage improvements that have moved CIGS device efficiencies from 20% to 23.35% [1]. Based on a survey of CIGS companies at the beginning of the project, the single biggest breakthrough for the CIGS community would be a mechanistic understanding of the role of alkalis in the material system. Significant accomplishments of Task 1: Alkali Science: 1) KF post-deposition treatments were shown to improve lifetime, open-circuit voltage (VOC), and efficiency of industrial partner samples, even when done as a later step, separate from the original CIGS deposition. 2) KF boosted efficiency when incorporated at the end of the third stage of NREL CIGS growth. 3) XPS characterization of CIGS surfaces with and without PDTs led to a proposed mechanism whereby K drives structural transformation at 350 degrees C that is locked in at room temperature even after K is rinsed away. 4) Published recipes for KF and RbF PDTs. Literature to date did not provide enough detail to quickly reproduce experimental results. 5) Identified most important parameters (RbF cell temperature and lamp setpoint temperature) and set boundaries for successful RbF PDTs. The purpose of Task 2: Cell-level Reliability was to overcome the largest challenges to investor confidence and long product lifetime in CIGS-based photovoltaic products: metastability, shading-induced hot spots, and potential-induced degradation (PID). Key findings were made in each of these areas by studying CIGS reliability at the cell level: 1) Published NREL's cell-level reliability testing procedures along with challenges that were encountered while developing them. These were also distributed to the community through an MRS conference presentation. 2) Decreased metastability by adding a CdS hole-injection layer between the CIGS and Zn(O,S) in the device stack. It also improved device performance. Materials other than CdS can be used for the same purpose. 3) Reduced front-glass PID by replacing soda-lime glass with low-Na borosilicate glass. 4) Found that PID depends on leakage current and light/electrical bias. This will help labs avoid test-specific degradation. 5) Discovered that CIGS can suffer from two different types of PID with different mechanisms. Front is slower and leads to shunting ZnO. Back is faster and degrades the p-n junction. 6) Holding cells at open circuit slows PID compared to short circuit. This affects testing protocols for glass/glass modules.

14 SOLAR ENERGY↗

Space shuttle orbiter windshield system design and test

The development and testing of primary structural elements that are necessary to design a windshield system for the space shuttle orbiter are summarized. The elements include the outer (heat shield) panes, the inner pressure panes, the seals for both panes, and components of both window frames. One test article representing a pressure pane, including frames and seals, was tested under two sets of conditions. One set represented 100 mission cycles with temperature and pressure typical of those exerted on the innermost pane of the three-pane window system, and the second set represented 100 mission cycles with temperature and pressure typical of those exerted on a middle pane. A second test article representing an outer (heat sheild) pane was tested to conditions of 120 entry cycles, which equates to 100 entry cycles plus sufficient fatigue on the pane to account for 100 boost cycles. All elements of the design survived the test conditions in good condition. Window system for the shuttle orbiter vehicle.

Hayashida, K.↗