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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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Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer
Deep learning has contributed to major advances in the prediction of protein structure from sequence, a fundamental problem in structural bioinformatics. With predictions now approaching the accuracy of crystallographic experiments, and with accelerators like GPUs and TPUs making inference using large models rapid, genome-level structure prediction becomes an obvious aim. Leadership-class computing resources can be used to perform genome-scale protein structure prediction using state-of-the-art deep learning models, providing a wealth of new data for systems biology applications. Here we describe our efforts to efficiently deploy the AlphaFold v.2 program, for full-proteome structure prediction, at scale on the Oak Ridge Leadership Computing Facility's resources, including the Summit supercomputer. We performed inference to produce the predicted structures for 40,526 protein sequences, corresponding to four prokaryotic proteomes and one plant proteome, using under 4,400 total Summit node hours, equivalent to using the majority of the supercomputer for a little over one hour. We also designed an optimized structure refinement that reduced the time for the relaxation stage of the AlphaFold pipeline by over 10X for longer sequences. We demonstrate the types of analyses that can be performed on proteome-scale collections of sequences, including a search for novel quaternary structures and implications for functional annotation.
An across-the-bay flight support structure designed specifically for the Spartan program
The preliminary design of an across-the-bay Flight Support Structure optimized to the specific requirements of the Spartan program has been completed. Although approximately 15 percent heavier than the initial goal, preliminary analysis indicate very low stress levels and significant reduction in weight should be possible in the final design. This structure is capable of supporting two Spartan 200-class spacecraft or attached payloads of equivalent total weight. The inherent structural efficiency of monocoque type construction is utilized. The minimization of fabrication and assembly costs and provision for simple and versatile payload interfacing where given significant considerations. Modularity of this structure allows it to be readily adapted for use as the primary structure of an Aries-class Spartan free-flyer utilizing the Orbit trunning latch mechanisms, thus eliminating the need for a flight support structure.
Buckling analysis and test correlation of hat stiffened panels for hypersonic vehicles
The paper discusses the design, analysis, and test of hat stiffened panels subjected to a variety of thermal and mechanical load conditions. The panels were designed using data from structural optimization computer codes and finite element analysis. Test methods included the grid shadow moire method and a single gage force stiffness method. The agreement between the test data and analysis provides confidence in the methods that are currently being used to design structures for hypersonic vehicles. The agreement also indicates that post buckled strength may potentially be used to reduce the vehicle weight.
Analysis of the optimal laminated target made up of discrete set of materials
A new class of problems was analyzed to estimate an optimal structure of laminated targets fabricated from the specified set of homogeneous materials. An approximate description of the perforation process is based on the model of radial hole extension. The problem is solved by using the needle-type variation technique. The desired optimization conditions and quantitative/qualitative estimations of optimal targets were obtained and are discussed using specific examples.
A Structured Quasi-Newton Algorithm for Optimizing with Incomplete Hessian Information
We present a structured quasi-Newton algorithm for unconstrained optimization problems that have unavailable second-order derivatives or Hessian terms. We provide a formal derivation of the well-known Broyden--Fletcher--Goldfarb--Shanno (BFGS) secant update formula that approximates only the missing Hessian terms, and we propose a linesearch quasi-Newton algorithm based on a modification of Wolfe conditions that converges to first-order optimality conditions. We also analyze the local convergence properties of the structured BFGS algorithm and show that it achieves superlinear convergence under the standard assumptions used by quasi-Newton methods using secant updates. In conclusion, we provide a thorough study of the practical performance of the algorithm on the CUTEr suite of test problems and show that our structured BFGS-based quasi-Newton algorithm outperforms the unstructured counterpart(s).
Mechanics of intraply hybrid composites - Properties, analysis and design
A mechanics theory is developed for predicting the physical thermal, hygral and mechanical properties (including various strengths) of unidirectional intraply hybrid composites (UIHC) based on unidirectional properties of the constituent composites. Procedures are described which can use this theory in conjunction with composite mechanics computer codes and general purpose structural analysis finite element programs for the analysis/design of structural components made from intraply hybrid angleplied laminates (IHAL). Comparisons with limited data show that this theory predicts mechanical properties of UIHC and flexural stiffnesses of IHAL which are in good agreement with experimental data. The theory developed herein makes it possible to design and optimize structural components from IHAL based on a large class of available constituent fibers.
Small, Low Cost, Launch Capability Development
A recent explosion in nano-sat, small-sat, and university class payloads has been driven by low cost electronics and sensors, wide component availability, as well as low cost, miniature computational capability and open source code. Increasing numbers of these very small spacecraft are being launched as secondary payloads, dramatically decreasing costs, and allowing greater access to operations and experimentation using actual space flight systems. While manifesting as a secondary payload provides inexpensive rides to orbit, these arrangements also have certain limitations. Small, secondary payloads are typically included with very limited payload accommodations, supported on a non interference basis (to the prime payload), and are delivered to orbital conditions driven by the primary launch customer. Integration of propulsion systems or other hazardous capabilities will further complicate secondary launch arrangements, and accommodation requirements. The National Aeronautics and Space Administration's Marshall Space Flight Center has begun work on the development of small, low cost launch system concepts that could provide dedicated, affordable launch alternatives to small, high risk university type payloads and spacecraft. These efforts include development of small propulsion systems and highly optimized structural efficiency, utilizing modern advanced manufacturing techniques. This paper outlines the plans and accomplishments of these efforts and investigates opportunities for truly revolutionary reductions in launch and operations costs. Both evolution of existing sounding rocket systems to orbital delivery, and the development of clean sheet, optimized small launch systems are addressed.
Enabling Dedicated, Affordable Space Access Through Aggressive Technology Maturation
A recent explosion in nano-sat, small-sat, and university class payloads has been driven by low cost electronics and sensors, wide component availability, as well as low cost, miniature computational capability and open source code. Increasing numbers of these very small spacecraft are being launched as secondary payloads, dramatically decreasing costs, and allowing greater access to operations and experimentation using actual space flight systems. While manifesting as a secondary payload provides inexpensive rides to orbit, these arrangements also have certain limitations. Small, secondary payloads are typically included with very limited payload accommodations, supported on a non interference basis (to the prime payload), and are delivered to orbital conditions driven by the primary launch customer. Integration of propulsion systems or other hazardous capabilities will further complicate secondary launch arrangements, and accommodation requirements. The National Aeronautics and Space Administration's Marshall Space Flight Center has begun work on the development of small, low cost launch system concepts that could provide dedicated, affordable launch alternatives to small, risk tolerant university type payloads and spacecraft. These efforts include development of small propulsion systems and highly optimized structural efficiency, utilizing modern advanced manufacturing techniques. This paper outlines the plans and accomplishments of these efforts and investigates opportunities for truly revolutionary reductions in launch and operations costs. Both evolution of existing sounding rocket systems to orbital delivery, and the development of clean sheet, optimized small launch systems are addressed. A launch vehicle at the scale and price point which allows developers to take reasonable risks with new propulsion and avionics hardware solutions does not exist today. Establishing this service provides a ride through the proverbial "valley of death" that lies between demonstration in laboratory and flight environments. This effort will provide the framework to mature both on-orbit and earth-to-orbit avionics and propulsion technologies while also providing dedicated, affordable access to LEO for cubesat class payloads.
Optimization of Blended Wing Body Composite Panels Using Both NASTRAN and Genetic Algorithm
The blended wing body (BWB) is a concept that has been investigated for improving the performance of transport aircraft. A trade study was conducted by evaluating four regions from a BWB design characterized by three fuselage bays and a 400,000 lb. gross take-off weight (GTW). This report describes the structural optimization of these regions via computational analysis and compares them to the baseline designs of the same construction. The identified regions were simplified for use in the optimization. The regions were represented by flat panels having appropriate classical boundary conditions and uniform force resultants along the panel edges. Panel-edge tractions and internal pressure values applied during the study were those determined by nonlinear NASTRAN analyses. Only one load case was considered in the optimization analysis for each panel region. Optimization was accomplished using both NASTRAN solution 200 and Genetic Algorithm (GA), with constraints imposed on stress, buckling, and minimum thicknesses. The NASTRAN optimization analyses often resulted in infeasible solutions due to violation of the constraints, whereas the GA enforced satisfaction of the constraints and, therefore, always ensured a feasible solution. However, both optimization methods encountered difficulties when the number of design variables was increased. In general, the optimized panels weighed less than the comparable baseline panels.
Theoretical study of the bonding of Sc, Y, and La singly charged and dipositive ions to C2H2, C2H4, and C3H6
The interaction of the Sc and Y singly-charged and dipositive ions with C2H2, C2H4, and C3H6 is studied using electronic structure calculations that include high levels of electron correlation. These results are compared with comparable calculations performed previously for La(+) and La(2+). For C2H2 and C2H4, all three metal ions insert into the C-C pi bond, making a three-membered ring. The optimal structures for the MC3H6(+) ions all involve rearrangement to make a four-membered ring. The strength of the metal-ligand bond for the singly charged ions follows the order La greater than Sc equal to about Y. In contrast, the bonds involving the dipositive ions are electrostatic, so that the binding energy increases as the size of the ion decreases, leading to the trend Sc greater than Y greater than La.
Tensegrity and mechanoregulation: from skeleton to cytoskeleton
OBJECTIVE: To elucidate how mechanical stresses that are applied to the whole organism are transmitted to individual cells and transduced into a biochemical response. DESIGN: In this article, we describe fundamental design principles that are used to stabilize the musculoskeletal system at many different size scales and show that these design features are embodied in one particular form of architecture that is known as tensegrity. RESULTS: Tensegrity structures are characterized by use of continuous tension and local compression; architecture, prestress (internal stress prior to application of external force), and triangulation play the most critical roles in terms of determining their mechanical stability. In living organisms, use of a hierarchy of tensegrity networks both optimizes structural efficiency and provides a mechanism to mechanically couple the parts with the whole: mechanical stresses applied at the macroscale result in structural rearrangements at the cell and molecular level. CONCLUSION: Due to use of tensegrity architecture, mechanical stress is concentrated and focused on signal transducing molecules that physically associate with cell surface molecules that anchor cells to extracellular matrix, such as integrins, and with load-bearing elements within the internal cytoskeleton and nucleus. Mechanochemical transduction may then proceed through local stress-dependent changes in molecular mechanics, thermodynamics, and kinetics within the cell. In this manner, the entire cellular response to stress may be orchestrated and tuned by altering the prestress in the cell, just as changing muscular tone can alter mechanical stability and structural coordination throughout the whole musculoskeletal system.
A geometric representation scheme suitable for shape optimization
A geometric representation scheme is outlined which utilizes the natural design variable concept. A base configuration with distinct topological features is created. This configuration is then deformed to define components with similar topology but different geometry. The values of the deforming loads are the geometric entities used in the shape representation. The representation can be used for all geometric design studies; it is demonstrated here for structural optimization. This technique can be used in parametric design studies, where the system response is defined as functions of geometric entities. It can also be used in shape optimization, where the geometric entities of an original design are modified to maximize performance and satisfy constraints. Two example problems are provided. A cantilever beam is elongated to meet new design specifications and then optimized to reduce volume and satisfy stress constraints. A similar optimization problem is presented for an automobile crankshaft section. The finite element method is used to perform the analyses.
First-principles calculations and experimental studies of: XYZ 2 thermoelectric compounds: Detailed analysis of van der Waals interactions
First-principles calculations can accelerate the search for novel high-performance thermoelectric materials. However, the prediction of the thermoelectric properties is strongly dependent on the approximations used for the calculations. Here, thermoelectric properties were calculated with different computational approximations ( i.e. , PBE-GGA, HSE06, spin–orbit coupling and DFT-D3) for three layered XYZ 2 compounds (TmAgTe 2 , YAgTe 2 , and YCuTe 2 ). In addition to the computations, the structural, electrical and thermal properties of these compounds were measured experimentally and compared to the computations. Furthermore, an enhanced prediction of the crystal structure and heat capacity was achieved with the inclusion of van der Waals interactions due to more accurate modeling of the interatomic forces. In particular, a large shift of the acoustic phonons and low-frequency optical phonons to lower frequencies was observed from the dispersion-optimized structure. From the phonon dispersion curves of these compounds, the ultralow thermal conductivity in the investigated XYZ 2 compounds could be described by a recent developed minimum thermal conductivity model. Additionally, for the prediction of the electrical conductivity, a temperature-dependent relaxation time was used, and it was limited by acoustic phonons. While HSE06 has only a small influence on the electrical properties due to a computed band gap energy of >0.25 eV, the inclusion of both van der Waals interactions and spin–orbit coupling leads to a more accurate band structure, resulting in better prediction of electrical properties. Furthermore, the experimental thermoelectric properties of YAgTe 2 , TmAg 0.95 Zn 0.05 Te 2 and TmAg 0.95 Mg 0.05 Te 2 were measured, showing an increase in zT of TmAg 0.95 Zn 0.05 Te 2 by more than 35% ( zT = 0.47 ± 0.12) compared to TmAgTe 2 .
Combined Experimental and Computational Study of Molybdenum and Niobium for Nuclear Sensor Application
Due to their novel electromagnetic and thermal properties, molybdenum (Mo) and niobium (Nb) become optimal temperature sensor materials for nuclear energy applications. We leveraged voltage recorded during a heat ramp to tune a computational method to predict the Seebeck electromotive force (EMF) of Mo and Nb. Using a combined Density Functional Theory (DFT) and Boltzmann Transport Equations (BTE) method the voltage was predicted but did not include the effects of temperature on atomic structure. Combining Ab Initio Molecular Dynamics (AIMD) and BTE included temperature effects on structure optimization and yielded voltages in a good agreement with experiment. Lanthanum (La) and Phosphorus (P) additives in Mo and Nb, respectively, could increase the EMF compared to those of the pure metals. The presence of oxygen (O) in Mo increases the EMF while O in Nb slightly reduces the EMF. Furthermore, our studies suggested that heat treatment-induced structural changes that lead to a reduction in voltage occur not only at the mesoscale as previously understood but also at the atomic scale.
Insights into Supported Subnanometer Catalysts Exposed to CO via Machine-Learning-Enabled Multiscale Modeling
Subnanometer catalysts offer high noble metal utilization and superior performance for several reactions. However, understanding their structures and properties on an atomic scale under working conditions is challenging due to the large configurational space. Here, we introduce an efficient multiscale framework to predict their stability exposed to an adsorbate. The framework integrates a comprehensive toolset including density functional theory (DFT) calculations, cluster expansion, machine learning, and structure optimization. The end-to-end machine-learning workflow guides DFT data generation and enables significant computational acceleration. We demonstrate the approach for CO-adsorbed Pdn (n = 1–55) clusters on CeO 2 (111). Simulation results reveal that CO can facilitate restructuring by stabilizing smaller planar structures and bilayer structures of specific intermediate sizes, consistent with experimental reports. Metal–support interactions, preferential CO adsorption, and metal nuclearity and structure control catalyst stability. As a result, the framework allows automatic discovery of stable catalyst structures and a systematic strategy to exploit properties in the subnanometer scale.
Military engine computational structures technology
Integrated High Performance Turbine Engine Technology Initiative (IHPTET) goals require a strong analytical base. Effective analysis of composite materials is critical to life analysis and structural optimization. Accurate life prediction for all material systems is critical. User friendly systems are also desirable. Post processing of results is very important. The IHPTET goal is to double turbine engine propulsion capability by the year 2003. Fifty percent of the goal will come from advanced materials and structures, the other 50 percent will come from increasing performance. Computer programs are listed.
Additive Manufacturing of Energy Harvesting Material System for Active Wireless MEMS Sensors
Combustion systems make up a large sum of the world’s yearly energy production despite advances in renewable energy sources. Precise control of pressure and temperature in combustion chambers allows for lower carbon emissions, and overall higher efficiency. Wireless temperature and pressure sensors are critical for the operation of combustion chambers. Energy harvesters have emerged as a viable way to power wireless sensors when heat and mechanical energy are available. Lithium niobate (LNB), barium titanate (BTO), and lead zirconate titanate (PZT) pyroelectric ceramics were studied and fabricated through additive manufacturing (AM) for use as energy harvesting structures in combustion environments. The electric power generation potential of LNB and PZT ceramics was studied by varying the temperature from 50 to 60 °C and by introducing cyclic compression loads of 2000 N amplitude. It was found that thermal energy conversion had the highest output of 500 nW and that combined thermal and mechanical conversion did not increase the harvesting potential because of the competing contributions of both effects. Powder bed and slurry extrusion AM methods were used to fabricate BTO and PZT ceramic structures. Optimization of the powder-based binder jetting method produced BTO ceramics with a relative density of 36.77% a piezoelectric coefficient of 153 pC/N. The density of the ceramics increased up to 56% when increasing the saturation of binder in the powder to because of liquid phase sintering. Finally, PZT structures were manufactured through AM and fin features were added to the design to enhance the heat transfer along the material. The harvested power density of the flat samples was 3.643 μW/cm 3 and of the finned samples was 3.034 μW/cm3. This research paves the ways for the development of self-powered wireless sensors in critical areas of operation such as combustion.