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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CP-DSSS: A Novel Waveform for Multiple Access in IoT

Cyclic prefix direct sequence spread spectrum (CPDSSS) is a novel waveform with versatile characteristics that positions itself well as a secondary network to relieve the congested wireless spectrum. The underlying structure of CPDSSS allows for efficient and effective multi-access capabilites through frequency and time division schemes in a given system. The sum-rate capacity of the system is maximized when the spectrum is divided and allocated to users with the best signal-to-noise (SNR) ratio for the given channel slice. We propose an algorithm for dividing and allocating portions of the spectrum to multiple users with the final goal of maximizing the sumrate capacity of the network. We also propose and develop a precoding/equalization technique that reduces the length of the channel impulse response. This, when used along with a matched filter detector, leads to some improvement in the sum-rate capacity of the network

5G and Beyond Communications↗
DOE OSTI2017

Thin Film Approaches to the SRF Cavity Problem Fabrication and Characterization of Superconducting Thin Films

Superconducting Radio Frequency (SRF) cavities are responsible for the acceleration of charged particles to relativistic velocities in most modern linear accelerators, such as those employed at high-energy research facilities like Thomas Jefferson National Laboratory’s CEBAF and the LHC at CERN. Recognizing SRF as primarily a surface phenomenon enables the possibility of applying thin films to the interior surface of SRF cavities, opening a formidable tool chest of opportunities by combining and designing materials that offer greater performance benefit. Thus, while improvements in radio frequency cavity design and refinements in cavity processing techniques have improved accelerator performance and efficiency – 1.5 GHz bulk niobium SRF cavities have achieved accelerating gradients in excess of 35 MV/m – there exist fundamental material bounds in bulk superconductors limiting the maximally sustained accelerating field gradient (≈ 45 MV/m for Nb) where inevitable thermodynamic breakdown occurs. With state of the art Nb based cavity design fast approaching these theoretical limits, novel material innovations must be sought in order to realize next generation SRF cavities. One proposed method to improve SRF performance is to utilize thin film superconducting-insulating-superconducting (SIS) multilayer structures to effectively magnetically screen a bulk superconducting layer such that it can operate at higher field gradients before suffering critically detrimental SRF losses. This dissertation focuses on the production and characterization of thin film superconductors for such SIS layers for radio frequency applications. Correlated studies on structure, surface morphology and superconducting properties of epitaxial Nb and MgB2 thin films are presented.

Beringer, Douglas↗
NASA NTRS1975

Propellers of Minimum Induced Loss, and Water Tunnel Tests of Such a Propeller

The fundamental vortex theory for a single rotation propeller with a finite number of blades is reviewed. The theory leads to the specification of a radial distribution of bound circulation on each blade for minimum induced loss, analogous to the elliptic spanwise distribution of bound circulation on a wing for minimum induced drag. A propeller designed in accord with this theory has been tested in a water tunnel where it exhibited high efficiency in spite of localized cavitating flow. A knowledge of the flow field for an optimum propeller is of value to the airframe designer seeking to maximize the performance of the airplane-propeller combination.

Larrabee, E. E.↗
NASA NTRS2004

Cardiovascular Countermeasures for Exploration-Class Space Flight Missions

Astronaut missions to Mars may be many years or even decades in thc future but current and planned efforts can be extrapolated to required treatments and prophylaxis for delerious efforts of prolonged space flight on the cardiovascular system. The literature of candidate countermeasures was considered in combination with unpublished plans for countermeasure implementation. The scope of cardiovascular countermeasures will be guided by assessments of the efficacy of mechanical, physiological and pharmacological approaches in protecting the cardiovascular capacities of interplanetary crewmembers. Plans for countermeasure development, evaluation and validation will exploit synergies among treatment modalities with the goal of maximizing protective effects while minimizing crew time and in-flight resource use. Protection of the cardiovascular capacity of interplanetary crewmembers will become more effective and efficient over the next few decades, but trade-offs between cost and effectiveness of efficiency are always possible if the increased level of risk can be accepted.

Charles, John B.↗
NASA NTRS2014

Cutting More than Metal: Breaking the Development Cycle

New technology is changing the way we do business at NASA. The ability to use these new tools is made possible by a learning culture able to embrace innovation, flexibility, and prudent risk tolerance, while retaining the hard-won lessons learned of other successes and failures. Technologies such as 3-D manufacturing and structured light scanning are re-shaping the entire product life cycle, from design and analysis, through production, verification, logistics and operations. New fabrication techniques, verification techniques, integrated analysis, and models that follow the hardware from initial concept through operation are reducing the cost and time of building space hardware. Using these technologies to be more efficient, reliable and affordable requires we bring them to a level safe for NASA systems, maintain appropriate rigor in testing and acceptance, and transition new technology. Maximizing these technologies also requires cultural acceptance and understanding and balancing rules with creativity. Evolved systems engineering processes at NASA are increasingly more flexible than they have been in the past, enabling the implementation of new techniques and approaches. This paper provides an overview of NASA Marshall Space Flight Center's new approach to development, as well as examples of how that approach has been incorporated into NASA's Space Launch System (SLS) Program, which counts among its key tenants - safety, affordability, and sustainability. One of the 3D technologies that will be discussed in this paper is the design and testing of various rocket engine components.

Singer, Chris↗
DOE OSTI2021

Efficient Active Learning for Gaussian Process Classification by Error Reduction

Active learning sequentially selects the best instance for labeling by optimizing an acquisition function to enhance data/label efficiency. The selection can be either from a discrete instance set (pool-based scenario) or a continuous instance space (query synthesis scenario). In this work, we study both active learning scenarios for Gaussian Process Classification (GPC). The existing active learning strategies that maximize the Estimated Error Reduction (EER) aim at reducing the classification error after training with the new acquired instance in a onestep-look-ahead manner. The computation of EER-based acquisition functions is typically prohibitive as it requires retraining the GPC with every new query. Moreover, as the EER is not smooth, it can not be combined with gradient-based optimization techniques to efficiently explore the continuous instance space for query synthesis. To overcome these critical limitations, we develop computationally efficient algorithms for EER-based active learning with GPC. Further, we derive the joint predictive distribution of label pairs as a one-dimensional integral, as a result of which the computation of the acquisition function avoids retraining the GPC for each query, remarkably reducing the computational overhead. We also derive the gradient chain rule to efficiently calculate the gradient of the acquisition function, which leads to the first query synthesis active learning algorithm implementing EER-based strategies. Our experiments clearly demonstrate the computational efficiency of the proposed algorithms. We also benchmark our algorithms on both synthetic and real-world datasets, which show superior performance in terms of sampling efficiency compared to the existing state-of-the-art algorithms.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

Efficient Simulation Budget Allocation for Selecting an Optimal Subset

We consider a class of the subset selection problem in ranking and selection. The objective is to identify the top m out of k designs based on simulated output. Traditional procedures are conservative and inefficient. Using the optimal computing budget allocation framework, we formulate the problem as that of maximizing the probability of correc tly selecting all of the top-m designs subject to a constraint on the total number of samples available. For an approximation of this corre ct selection probability, we derive an asymptotically optimal allocat ion and propose an easy-to-implement heuristic sequential allocation procedure. Numerical experiments indicate that the resulting allocatio ns are superior to other methods in the literature that we tested, and the relative efficiency increases for larger problems. In addition, preliminary numerical results indicate that the proposed new procedur e has the potential to enhance computational efficiency for simulation optimization.

Chen, Chun-Hung↗
DOE OSTI2018

An In 0.42 Ga 0.58 N tunnel junction nanowire photocathode monolithically integrated on a nonplanar Si wafer

Group III-nitride semiconductors exhibit many ideal characteristics for solar water splitting, including a tunable energy bandgap across nearly the entire solar spectrum and suitable band edge positions for water oxidation and proton reduction under visible and near-infrared light irradiation. To date, however, the best reported energy conversion efficiency for III-nitride semiconductor photocathodes is still below 1%. Here we report on the demonstration of a relatively efficient p-type In 0.42 Ga 0.58 N photocathode, which is monolithically integrated on an n-type nonplanar Si wafer through a GaN nanowire tunnel junction. The open pillar design, together with the nonplanar Si wafer can significantly maximize light trapping, whereas the tunnel junction reduces the interfacial resistance and enhances the extraction of photo-generated electrons. In addition, photodeposited Pt nanoparticles on InGaN nanowire surfaces significantly improve the cathodic performance. The nanowire photocathode exhibits a photocurrent density of 12.3 mA cm -2 at 0 V vs. RHE and an onset potential of 0.79 V vs. RHE under AM 1.5G one-sun illumination. Here, the maximum applied bias photon-to-current efficiency reaches 4% at ~0.52 V vs. RHE, which is one order of magnitude higher than the previously reported values for III-nitride photocathodes. Significantly, no performance degradation was measured for over 30 hours solar water splitting with a steady photocurrent density ~12 mA cm -2 without using any extra surface protection, which is attributed to the spontaneous formation of N-terminated surfaces of InGaN nanowires to protect against photocorrosion.

42 ENGINEERING↗
DOE OSTI2021

Synergistic Improvement of Carbohydrate and Lignin Processability by Biomimicking Biomass Processing

The sustainability and economic feasibility of modern biorefinery depend on the efficient processing of both carbohydrate and lignin fractions for value-added products. By mimicking the biomass degradation process in white-rote fungi, a tailored two-step fractionation process was developed to maximize the sugar release from switchgrass biomass and to optimize the lignin processability for bioconversion. Biomimicking biomass processing using Formic Acid: Fenton: Organosolv (F 2 O) and achieved high processability for both carbohydrate and lignin. Specifically, switchgrass pretreated by the F 2 O process had 99.6% of the theoretical yield for glucose release. The fractionated lignin was also readily processable by fermentation via Rhodococcus opacus PD630 with a lipid yield of 1.16 g/L. Scanning electron microscope analysis confirmed the fragmentation of switchgrass fiber and the cell wall deconstruction by the F 2 O process. 2D-HSQC NMR further revealed the cleavage of aryl ether linkages (β-O-4) in lignin components. These results revealed the mechanisms for efficient sugar release and lignin bioconversion. The F 2 O process demonstrated effective mimicking of natural biomass utilization system and paved a new path for improving the lignin and carbohydrate processability in next generation lignocellulosic biorefinery.

09 BIOMASS FUELS↗
DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Efficient Distributed Optimization of Wind Farms Using Proximal Primal-Dual Algorithms

This paper presents a distributed approach to performing real-time optimization of large wind farms. Wind turbines in a wind farm typically operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. This paper optimizes the overall power produced by a wind farm by formulating and solving a nonconvex optimization problem where the yaw angles are optimized to allow some turbines to operate in misaligned conditions and shape the aerodynamic interactions in a favorable way. The solution of the nonconvex smooth problem is tackled using a proximal primal-dual gradient method, which provably identifies a first-order stationary solution in a global sublinear manner. By adding auxiliary optimization variables for every pair of turbines that are coupled aerodynamically, and properly adding consensus constraints into the underlying problem, a distributed algorithm with turbine-to-turbine message passing is obtained; this allows for turbines to be optimized in parallel using local information rather than information from the whole wind farm. This algorithm is computationally light, as it involves closed-form updates. This approach is demonstrated on a large wind farm with 60 turbines. The results indicate that similar performance can be achieved as with finite-difference gradient-based optimization at a fraction of the computational time and thus approaching real-time control/optimization.

17 WIND ENERGY↗
NASA NTRS2001

Additive Runge-Kutta Schemes for Convection-Diffusion-Reaction Equations

Additive Runge-Kutta (ARK) methods are investigated for application to the spatially discretized one-dimensional convection-diffusion-reaction (CDR) equations. First, accuracy, stability, conservation, and dense output are considered for the general case when N different Runge-Kutta methods are grouped into a single composite method. Then, implicit-explicit, N = 2, additive Runge-Kutta ARK2 methods from third- to fifth-order are presented that allow for integration of stiff terms by an L-stable, stiffly-accurate explicit, singly diagonally implicit Runge-Kutta (ESDIRK) method while the nonstiff terms are integrated with a traditional explicit Runge-Kutta method (ERK). Coupling error terms are of equal order to those of the elemental methods. Derived ARK2 methods have vanishing stability functions for very large values of the stiff scaled eigenvalue, z(exp [I]) goes to infinity, and retain high stability efficiency in the absence of stiffness, z(exp [I]) goes to zero. Extrapolation-type stage-value predictors are provided based on dense-output formulae. Optimized methods minimize both leading order ARK2 error terms and Butcher coefficient magnitudes as well as maximize conservation properties. Numerical tests of the new schemes on a CDR problem show negligible stiffness leakage and near classical order convergence rates. However, tests on three simple singular-perturbation problems reveal generally predictable order reduction. Error control is best managed with a PID-controller. While results for the fifth-order method are disappointing, both the new third- and fourth-order methods are at least as efficient as existing ARK2 methods while offering error control and stage-value predictors.

Kennedy, Christopher A.↗
DOE OSTI2015

Structural changes and self-activated photoluminescence in reductively annealed Sr{sub 3}AlO{sub 4}F

White light emission of self-activated photoluminescence (PL) in Sr{sub 3}AlO{sub 4}F under 254 nm light is only observed after annealing in a reducing atmosphere of 5%H{sub 2}/95%Ar. High-resolution neutron powder diffraction reveals that the FSr{sub 6} octahedrons and AlO{sub 4} tetrahedrons in this anti-perovskite structure are closer packed in reduced than in air-annealed samples which show no PL. Careful analysis of temperature-dependent neutron powder diffraction data establishes smaller isotropic displacement parameters for Sr(1) and O in Sr{sub 3}AlO{sub 4}F annealed in a reducing atmosphere indicating that the denser packing of the polyhedral sub-units leads to a slightly deeper potential for the Sr(1) and O atoms. Both the air- and reductively-annealed samples have identical thermal expansion within the temperature range between 3 and 350 K. The Debye temperatures were calculated using the atomic displacement parameters and show no significant differences between the air and reductively annealed samples making the Debye temperature a bad proxy for self-activated PL. - Graphical abstract: Annealing Sr{sub 3}AlO{sub 4}F under reducing conditions results in an intense self-activated photoluminescence which is correlated with a denser packing of FSr{sub 6} and AlO{sub 4} polyhedra. - Highlights: • Sr{sub 3}AlO{sub 4}F made in air does not show self-activated photoluminescence. • Only when annealing Sr{sub 3}AlO{sub 4}F in a reducing gas is photoluminescence observed. • FSr{sub 6} and AlO{sub 4} polyhedra in reduced Sr{sub 3}AlO{sub 4}F structure are packed more efficient. • Smaller displacement parameters are found for under-bonded Sr(1) and O sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Direct Conversion of Syngas-to-Hydrocarbons over Higher Alcohols Synthesis Catalysts Mixed with HZSM-5

The synthesis of hydrocarbon fuels directly from synthesis gas (i.e. one step process) was investigated with a catalytic system comprised of HZSM-5 physically mixed with either a methanol synthesis catalyst or a higher alcohols synthesis (HAS) catalyst. The metal sites of the methanol or HAS synthesis catalyst enable the conversion of syngas to alcohols, whereas HZSM-5 provides acid sites required for methanol dehydration, and dimethyl ether-to-hydrocarbons reactions. Catalytic performance for HZSM-5 when mixed with either a 5 wt.% Pd/ZnO/Al2O3 methanol synthesis catalyst or a HAS catalyst was evaluated at 300°C, 70 bars, GHSV=700 h-1 and H2/CO=1 using a HZSM-5: alcohols synthesis catalyst weight ratio of 3:1. The major difference observed between the methanol synthesis and HAS catalyst mixtures was found in the production of durene which is an undesirable byproduct. While durene formation is negligible with any of the HAS catalysts mixed with the HZSM-5 evaluated in this study, it represents almost 50% of the C5+ fraction for the methanol synthesis catalyst (5 wt.% Pd/ZnO/Al2O3 ) mixed with HZSM-5. This presents an advantage for using HAS catalysts over the methanol synthesis catalyst to minimize the durene by-product. The yield toward the desired C5+ hydrocarbons is thus twice higher with selected HAS catalysts as compared to when HZSM-5 is mixed with 5 wt.% Pd/ZnO/Al2O3. Among all the HAS catalysts evaluated in this study, a catalyst with 0.5 wt.% Pd/FeCoCu catalyst was found the most promising due to higher production of C5+ hydrocarbons and low durene formation. The efficiency of the one-step process was thus further evaluated using the HZSM-5: 0.5 wt.% Pd/FeCoCu catalyst mixture under a number of process conditions to maximize liquid hydrocarbons product yield. At 300oC, 70 bars, GHSV = 700 h-1 and HZSM-5: 0.5 wt.% Pd/FeCoCu = 3:1 (wt.), the C5+ fraction represents 48.5% of the hydrocarbons. Unfortunately, it is more difficult to achieve higher selectivity to desired C5+ hydrocarbons as the formation of CO2, CH4, and other light hydrocarbons is challenging to suppress in the presence of mixed metal and acid sites. When the 0.5 wt.% Pd/FeCoCu and HZSM-5 are operated sequentially by way of a two-step process the C5+ hydrocarbons fraction is lower and represents 30.4% of the hydrocarbons under comparable conditions. The yield toward the C5+ hydrocarbons is twice higher for the one-step process due to an improved CO conversion and higher C5+ hydrocarbons fraction. The main advantage of the one-step process is that higher syngas conversion can be achieved as the equilibrium-driven conversion limitations for methanol and dimethyl ether are removed since they are intermediates to the final hydrocarbons product.

alcohols-to-hydrocarbons↗
DOE OSTI2025

Anomaly Detection Based on Machine Learning for the CMS Electromagnetic Calorimeter Online Data Quality Monitoring

Using a semi-supervised machine learning approach we present a real-time anomaly detection system based on an autoencoder used for online data quality monitoring of the CMS electromagnetic calorimeter operating at the CERN LHC. We introduce a novel method that maximizes the anomaly detection performance making use of the time-dependence of anomalies and the spatial variations in the detector response. The autoencoder-based system efficiently detects anomalies in real time and maintains a very low false discovery rate. We validate the performance of this novel system with anomalies from LHC collision data taken in 2018 and 2022. In addition, results are presented after deploying the autoencoder-based system in the CMS online Data Quality Monitoring workflow at the beginning of LHC Run 3 resulting in the system to detect issues that were missed by the existing system.

Harilal, Abhirami [Carnegie Mellon University, Pit↗
DOE OSTI2014

Effects of q-profile structure on turbulence spreading: A fluctuation intensity transport analysis

This paper studies effects of q-profile structure on turbulence spreading. It reports results of numerical experiments using global gyrokinetic simulations. We examine propagation of turbulence, triggered by an identical linear instability in a source region, into an adjacent, linearly stable region with variable q-profile. The numerical experiments are designed so as to separate the physics of turbulence spreading from that of linear stability. The strength of turbulence spreading is measured by the penetration depth of turbulence. Dynamics of spreading are elucidated by fluctuation intensity balance analysis, using a model intensity evolution equation which retains nonlinear diffusion and damping, and linear growth. It is found that turbulence spreading is strongly affected by magnetic shear s, but is hardly altered by the safety factor q itself. There is an optimal range of modest magnetic shear which maximizes turbulence spreading. For high to modest shear values, the spreading is enhanced by the increase of the mode correlation length with decreasing magnetic shear. However, the efficiency of spreading drops for sufficiently low magnetic shear even though the mode correlation length is comparable to that for the case of optimal magnetic shear. The reduction of spreading is attributed to the increase in time required for the requisite nonlinear mode-mode interactions. The effect of increased interaction time dominates that of increased mode correlation length. Our findings of the reduction of spreading and the increase in interaction time at weak magnetic shear are consistent with the well-known benefit of weak or reversed magnetic shear for core confinement enhancement. Weak shear is shown to promote locality, as well as stability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Predicting radiative transport properties of plasma sprayed porous ceramics

The typical yttria-stabilized zirconia material for making the thermal barrier coatings (TBCs) is intrinsically semitransparent to thermal radiation, and the unique disordered microstructures in TBCs make them surprisingly highly scattering. To quantitatively understand the influence of disordered microstructures, this paper presents a quantitative prediction on the radiative properties, especially the transport scattering coefficient of plasma sprayed TBC based on microstructure analysis and rigorous electromagnetic theory. The impact of the porosity, shape, size, and orientation of different types of voids on transport scattering coefficient is comprehensively investigated under the discrete dipole approximation. An inverse model integrating these factors together is then proposed to quantitatively connect transport scattering coefficient with microstructural information, which is also validated by available experimental data. Afterwards, an optimization procedure is carried out based on this model to obtain the optimal size and orientation distribution of the microscale voids to achieve the maximal radiation insulation performance at different operating temperatures, providing guidelines for practical coating design and fabrication. This work suggests that the current model is effective and also efficient for connecting scattering properties to microstructures and can be implemented as a quantitative tool for further studies like non-destructive infrared imaging as well as micro/nanoscale thermal design of TBCs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A novel high frequency, high bandwidth, three phase Mach–Zehnder optical data link

In inertial confinement fusion, hydrogen isotopes are fused together under high pressures and temperatures. Typically, the duration of these experiments is incredibly short, on the order of around 60–150 ps. Due to the high radiation environment, a detector’s signal is typically data linked far distances to a protected location. The diagnostic challenge for fusion reaction history measurements is to measure signals of interest maximizing dynamic range while also maintaining time resolution on the order of 10 ps. In this work, we present a new experimental optical data link used to efficiently transport diagnostic signals over great distances to the recording system while not restricting the dynamic range. The concept of a three phase Mach–Zehnder modulator system is introduced as well as a description of the physical prototype. The initial results from testing at the OMEGA facility show that this system is a viable method for signal transportation.

47 OTHER INSTRUMENTATION↗