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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 991 records · Page 55

Enabling Additive Manufacturing Technologies for Advanced Aero Propulsion Materials & Components

Additive manufacturing (AM) technologies are enabling for advanced high performance, propulsion component designs in electric motors1-2 and turbine engine systems in future electrified aircraft. AM offers significant benefits over conventional manufacturing to fabricate components that are more compact, lighter weight, geometrically complex, innovatively cooled, integrated, multi-material, and multifunctional. For turbine engine applications, silicon carbide (SiC) based composites are being pursued using binder jetting and laminated object manufacturing (LOM) for components such as shrouds, vanes, and recuperators. For electric motor applications, additive processes are being applied toward optimized component designs to include the housing, rotor, and stators with 3-D printing and wire imbedded coils and with direct printed 3-phase coils. The electrical conductivity of silver conductor coils optimized by evaluating alternate sintering methods and additions of graphene and carbon nanostructures will be presented. Potential benefits of new electric motor components in improving temperature capability, efficiency, and power density for reductions in energy consumption and emissions will be discussed.

Halbig, Michael C.↗

Rapid, Approximate Multi-Axis Vibration Testing [Thesis]

The aerospace industry uses vibration shaker tables to perform component durability testing. In these tests a component, piece of equipment, or entire system is attached to a shaker table where it is subjected to dynamic excitation. The goal is to understand how the article under test will perform in its service environment without having to run it through its entire service life via field testing. In a vibration test, an aerospace system or component is qualified if it is shown to survive a test meant to replicate its lifetime service conditions. The test is designed based on recorded field data. To develop a test, a system is taken through all of its intended environments, e.g., transportation, launch, and reentry. Acceleration data measured from these environments is then brought back to the lab and imported into a shaker table controller. The controller then drives a vibration test intended to mimic the acceleration conditions experienced by the system or specific components of the system in the field. However, it is often difficult to match the measured field response in a lab test. This is largely due to the test’s boundary conditions and excitation methods. In a lab test, a shaker table is the excitation source. The two most common shaker table types, differentiated by their number of independent degrees of freedom, are single-axis and multi-axis shaker tables. Multi-axis shakers have the ability to reproduce service environments more realistically, as real accelerations inevitably produce multiple degrees of freedom of excitation simultaneously. Figure 1 depicts a generic multi-axis testing setup on a three-axis shaker table. Often multi-axis tests use six-degree-of-freedom (6DOF) shaker tables. Yet multi-axis shakers are not yet common in the aerospace industry due in part to their high cost and the difficulty for shaker controllers to handle the added complexity. Single-axis shaker tables are much more common. They are not as expensive to purchase and have a wide range of control software options.

42 ENGINEERING↗

MTL_TX: A Multi-Task Transformer Model for Improved Radiation Time-Series Estimation

Controlling radiation doses at potential radioactive facilities is critical to ensuring the safety of both personnel and the public. At the Thomas Jefferson National Accelerator Facility (JLab), multiple sensors are deployed around the three experimental halls to monitor key parameters, including single-beam current, energy levels, current leakage, and radiation values during accelerator operations. In this study, we developed a Multi-task Transformer model, MTL_TX, to accurately estimate radiation doses at sensor locations based on historical data, with the aim of enhancing safety in accelerator facilities and surrounding public areas. To improve estimation accuracy, we integrated two innovative components into the proposed model: hierarchical feature embedding (HFE) and multi-level decomposition attention (MDA). Additionally, the multi-task learning (MTL) framework effectively leverages correlations among multiple sensors, enabling individual estimations for each sensor. MTL_TX achieved outstanding results on data collected in 2018, with an MSE of 0.1464, an RMSE of 0.2353, and an R 2 score of 0.8584. Furthermore, when trained on 2018 data, MTL_TX exhibited excellent generalization capability to unseen datasets from 2016 to 2019, achieving an MSE of 0.1407, an RMSE of 0.2263, and an R 2 score of 0.8831. These results demonstrate a significant improvement over existing state-of-the-art models.

Transformer↗

Effect of Blown Powder Directed Energy Deposition Angle On Overspray Contamination

Abstract Blown powder directed energy deposition (DED) hybrid machine tools are particularly beneficial when the net shape of a component is to be manufactured in an additive and machined interleaved fashion. This investigation seeks to analyze the effect of the additive head lean angle relative to the part on blown powder DED surface contamination due to overspray. These hybrid DED platforms are commonly installed on multi-axis machining systems where the lean of the deposition head relative to the component surface can be controlled by tilting the component. The blown powder DED process has a 10–50% lower catchment efficiency as compared to wire fed DED systems. This excess powder is still fed towards the deposition location where the particles are heated by the laser and rebound off the melt pool. Some of these heated particles impact the previously machined thin-wall surface. While the deposition process and tool path planning process has been evaluated, the effect of the overspray due to lean angle of the deposition head on the previously thin-wall machined surface is not yet fully understood. This investigation found that minimum lean angle coincides with minimal overspray effect with nearly no contamination. If a lean angle is required, the maximum lean angle possible should be implemented for the smallest effected overspray area on the machined surface which was found to decrease the affect zone by half compared to intermediate lean angles. A diameter divergence was also noticed as the deposition angle was increased. In this study, a thorough analysis of the surface and geometric effects when depositing thin-walled components at varying angles is completed. It has been shown that part quality can be significantly affected by lean angle and thus must be incorporated as an additional design consideration in the manufacturing process.

Heinrich, Lauren↗

Ultra low background Micromegas detectors for BabyIAXO solar axion search

Abstract The International AXion Observatory (IAXO) is a large scale axion helioscope that will look for axions and axion-like particles produced in the Sun with unprecedented sensitivity. BabyIAXO is an intermediate experimental stage that will be hosted at DESY (Germany) and that will test all IAXO subsystems serving as a prototype for IAXO but at the same time as a fully-fledged helioscope with potential for discovery.One of the crucial components of the project is the ultra-low background X-ray detectors that will image the X-ray photons produced by axion conversion in the experiment. The baseline detection technology for this purpose are Micromegas (Microbulk) detectors. We will show the quest and the strategy to attain the very challenging levels of background targeted for BabyIAXO that need a multi-approach strategy coming from ground measurements, screening campaigns of components of the detector, underground measurements, background models, in-situ background measurements as well as powerful rejection algorithms. First results from the commissioning of the BabyIAXO prototype will be shown.

Instruments & Instrumentation↗

Coupled multi-disciplinary composites behavior simulation

The capabilities of the computer code CSTEM (Coupled Structural/Thermal/Electro-Magnetic Analysis) are discussed and demonstrated. CSTEM computationally simulates the coupled response of layered multi-material composite structures subjected to simultaneous thermal, structural, vibration, acoustic, and electromagnetic loads and includes the effect of aggressive environments. The composite material behavior and structural response is determined at its various inherent scales: constituents (fiber/matrix), ply, laminate, and structural component. The thermal and mechanical properties of the constituents are considered to be nonlinearly dependent on various parameters such as temperature and moisture. The acoustic and electromagnetic properties also include dependence on vibration and electromagnetic wave frequencies, respectively. The simulation is based on a three dimensional finite element analysis in conjunction with composite mechanics and with structural tailoring codes, and with acoustic and electromagnetic analysis methods. An aircraft engine composite fan blade is selected as a typical structural component to demonstrate the CSTEM capabilities. Results of various coupled multi-disciplinary heat transfer, structural, vibration, acoustic, and electromagnetic analyses for temperature distribution, stress and displacement response, deformed shape, vibration frequencies, mode shapes, acoustic noise, and electromagnetic reflection from the fan blade are discussed for their coupled effects in hot and humid environments. Collectively, these results demonstrate the effectiveness of the CSTEM code in capturing the coupled effects on the various responses of composite structures subjected to simultaneous multiple real-life loads.

Singhal, Surendra N.↗

RF design of APEX2 two-cell continuous-wave normal conducting photoelectron gun cavity based on multi-objective genetic algorithm

High brightness, high repetition rate electron beams are key components for optimizing the performance of next generation scientific instruments, such as MHz-class X-ray Free Electron Laser (XFEL) and Ultra-fast Electron Diffraction/Microscopy (UED/UEM). In the Advanced Photo-injector EXperiment (APEX)at Berkeley Lab, a photoelectron gun based on a 185.7 MHz normal conducting re-entrant RF cavity, has been proven to be a feasible solution to provide high brightness, high repetition rate electron beam for both XFEL and UED/UEM. Based on the success of APEX, a new electron gun system, named APEX2, has been under development to further improve the electron beam brightness. For APEX2, we have designed a new 162.5 MHz two-cell photoelectron gun and achieved a significant increase on the cathode launching field and the beam exit energy. For a fixed charge per bunch, these improvements will allow for the emittance reduction and hence to an increased beam brightness. The design of APEX2 gun cavity is a complex problem with multiple design goals and restrictions, some even competing each other. In conclusion, for a systematic and comprehensive search for the optimized cavity geometry, we have developed and implemented a novel optimization method based on the Multi-Objective Genetic Algorithm (MOGA).

47 OTHER INSTRUMENTATION↗

Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report)

This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.

42 ENGINEERING↗

High Velocity Joining of Multi-material Stacks Containing 3rd Generation Advanced High-Strength Stainless Steel and Aluminum Extrusion and Casting (Abstract)

Advanced lightweight materials, including multi-phase steels, aluminum extrusions and aluminum castings, have increasingly replaced mild steel to meet original equipment manufacturer (OEM) demand for increased fuel economy and crash-safety requirements. Third Generation (Gen 3) AHSS provides a superior combination of strength and ductility for crash energy management components in the vehicle body-in-white (BIW). Aluminum extrusions are widely used for bumper, door rocker panel, cradle and battery frame applications. Aluminum castings are increasingly being used in electric vehicles to provide part consolidation, weight saving and increased driving range. Rocker panels are, for example, an important component of the battery electric vehicle (BEV) body structure. The rocker panel serves several purposes, including structural support, crash resistance, protection for the vehicle's underbody and battery tray, and contributing to the overall aesthetics. In order to reduce weight, rocker panels are usually constructed using outer panels consisting of 3rd generation advanced high strength steels (AHSS) and an inner multicell aluminum extrusion structure for energy absorption which protects the batteries in a crash event. It is well known, however, that these material combinations provide significant challenges for joining and are susceptible to liquid metal embrittlement and loss of strength. The overall goal is to find a solution that addresses these challenges in order to produce multi-material vehicle components with reduced weight and minimal galvanic and recyclability issues. The approach being proposed here is to utilize a novel high velocity (HiVe) riveting and clinching technique recently demonstrated by Pacific Northwest National Laboratory (PNNL) to join (2T/3T) sheets of aluminum alloys and steel. This process will not only address the aforementioned challenges but also help significantly reduce the joining cycle time. This work will also demonstrate use of HiVe assemblies to be retrofitted to existing body-shop robots thus having minimal impact to existing body shop operations.

36 MATERIALS SCIENCE↗

Machine Learning-Based Investigation of the Associations between Residential Power Consumption and Weather Conditions

Machine learning feature selection analyses were conducted to understand the impact of various weather attributes on power electricity demand and its components in the northwest United States. Load profiles data were obtained from the Northwest Energy Efficiency Alliance (NEEA) and processed to yield hourly load profiles with the same temporal resolution as the weather conditions data obtained from the National Oceanic and Atmospheric Administration (NOAA) for representative weather stations. The data were divided into five seasons; for each season, for each load component, the influences of weather factors were evaluated and quantified using cross-correlation, principal component analysis, and mutual information evaluation; then predictive models were developed based on the ranked/screened factors using the regression tree (RT) approach. After multi-fold cross-validation, the optimal complexity/depth of the regress tree models is found to vary for different load components, and the prediction accuracy using RT and weather data can be higher than 80% for heating and refrigeration, or lower than 30% for vent and cooking. The study provides guidance on improvement of load profile generation, or even serves as a standalone predictive tool for approximating load profiles in balance authorities or climate zones where load profile data is absent.

load composite, load profiling, NEEA, mutual infor↗

Design of Circular, Square, Single, and Multi-layer Induction Coils for Electromagnetic Priming Using Inductance Estimates

Special induction coils used for electro magnetic priming of ceramic foam filters in liquid metal filtration have been designed using a combination of analytical and finite element modeling. Relatively simple empirical equations published by Wheeler in 1928 and 1982 have been used during the design process. The equations were found to accurately predict the z-component of the magnetic flux densities of both single- and multi-layer coils as verified both experimentally and by using COMSOL{sup ®} 5.1 multiphysics simulations.

36 MATERIALS SCIENCE↗

Emerging Themes and Future Directions of Multi-Sector Nexus Research and Implementation

Water, energy, and food are all essential components of human societies. Collectively, their respective resource systems are interconnected in what is called the “nexus”. There is growing consensus that a holistic understanding of the interdependencies and trade-offs between these sectors and other related systems is critical to solving many of the global challenges they present. While nexus research has grown exponentially since 2011, there is no unified, overarching approach, and the implementation of concepts remains hampered by the lack of clear case studies. Here, we present the results of a collaborative thought exercise involving 75 scientists and summarize them into 10 key recommendations covering: the most critical nexus issues of today, emerging themes, and where future efforts should be directed. We conclude that a nexus community of practice to promote open communication among researchers, to maintain and share standardized datasets, and to develop applied case studies will facilitate transparent comparisons of models and encourage the adoption of nexus approaches in practice.

54 ENVIRONMENTAL SCIENCES↗

Multi-scale ordering in highly stretchable polymer semiconducting films

Stretchable semiconducting polymers have been developed as a key component to enable skin-like wearable electronics, but their electrical performance must be improved to enable more advanced functionalities. Here, we report a solution processing approach that can achieve multi-scale ordering and alignment of conjugated polymers in stretchable semiconductors to substantially improve their charge carrier mobility. Using solution shearing with a patterned microtrench coating blade, macroscale alignment of conjugated-polymer nanostructures was achieved along the charge transport direction. In conjunction, the nanoscale spatial confinement aligns chain conformation and promotes short-range π–π ordering, substantially reducing the energetic barrier for charge carrier transport. As a result, the mobilities of stretchable conjugated-polymer films have been enhanced up to threefold and maintained under a strain up to 100%. This method may also serve as the basis for large-area manufacturing of stretchable semiconducting films, as demonstrated by the roll-to-roll coating of metre-scale films.

36 MATERIALS SCIENCE↗

Manufacturing Process Design of a Micro-Scale Liquid-Liquid Extractor and Multi-phase Separator

Advances in process innovation within the chemical process industry are impeded by the cost of producing new innovative components. In this paper, various manufacturing process routes were evaluated for scaling up a micro-scale liquid-liquid extractor and multi-phase separator capable of separating immiscible phases that are used for the extraction of a chemical product into a lower boiling point solvent to make downstream distillation easier. A manufacturing process design methodology was used to evaluate both photochemical machining and binder jetting as a means for producing the micropost arrays within the separator. Cost curves show that for a 0.3 mm deep micropost array, photochemical machining was found to be much cheaper than binder jetting. However, because binder jetting processes enable microposts with over 13 times higher depth-to-width aspect ratios, binder jetting was found to decrease the overall costs of the extractor/separator by more than half for a 500 barrel per day plant, with breakeven as low as 15 barrels per day. These economics were confirmed by building extractor/separator plates and characterizing them dimensionally and functionally. The binder jet plates were found to perform better than photochemical plates leading to the complete separation of the organic phase from water. The utilization of slower sintering cycles combined with surface grinding provided acceptable dimensional tolerances for the binder jet plates. Using pressurized air during depowdering improved the economics for the binder jetting process.

42 ENGINEERING↗

Eulerian-Eulerian large eddy simulation of two-phase dilute bubbly flows

An efficient mathematical model is presented for conducting large eddy simulation (LES) of turbulent bubbly flows at low gas hold-ups. The mathematical model is based on the filtered multi-fluid equations derived by application of the component-weighted volume-averaging process of each phase. A two-fluid model is applied to the filtered set of equations, yielding a more computationally tractable set of filtered equations. The filtered equations are formulated in generalized curvilinear coordinates to simulate turbulent gas-liquid bubbly flows in complex geometries. The Germano model is used to account for sub-grid turbulent stresses. The gas and liquid momentum equations are discretized with the hybrid staggered/non-staggered method. The performance of the developed mathematical model is demonstrated by simulating the benchmark test case of a turbulent gas-liquid bubbly flow in a rectangular bubble column. The accuracy of the proposed method is assessed via comparison with the experimental data and other numerical results in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An integrated coupling model for solving multiscale fluid-fluid coupling problems in SAM code

In this study, an integrated coupling method has been developed for solving multiscale fluid-fluid coupling problems in plant-scale safety analysis models in SAM (System Analysis Module) code. In this method, a higher-fidelity multi-dimensional (3D) flow module is used for reactor components of complex flow features (e.g., reactor core) and a lumped parameter one-dimensional (1D) flow module for plant-scale flow loops (e.g., primary loop pipe network), respectively. In this method, the 3D fluid equation/domain and 1D fluid equation/domain are tightly coupled at the residual level and solved simultaneously using the Newton’s method to overcome the convergence issues typically seen in existing approaches like separate domain approach, where the 3D fluid equation and 1D fluid equation are solved separately. Extensive and successful code verifications and demonstrations have been performed for this newly developed method. This new modeling approach significantly simplify the work flow in developing high-fidelity plant-scale safety analysis model, e.g. for pool-type reactors and pebble-bed reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Improved representation of black carbon mixing structures suggests stronger direct radiative heating

Black carbon significantly influences the Earth system because of its strong solar radiation absorption. However, its direct radiative effect remains poorly understood in current climate models, partly because current climate models oversimplify the diverse structures formed when black carbon mixes with other atmospheric components. Here we show that incorporating more realistic, multi-mixing-structure representations of black carbon increases the direct radiative effect. We find that aged black carbon particles, with thicker coatings and higher embedded fractions, enhance the direct radiative effect more efficiently. Using machine learning alongside the Community Earth System Model, we show that the direct radiative effect at the top of the atmosphere in regions with heavy black carbon pollution is 31.6% greater when multi-mixing structures are considered. These findings highlight the importance of modeling complex mixing structures of particle-resolved black carbon to accurately capture their warming impacts on global atmosphere, particularly in highly polluted regions.

54 ENVIRONMENTAL SCIENCES↗

MODE: A Web Application for Interactive Visualization and Exploration of Omics Data

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as “omics”) data allow researchers to find biomarkers or molecular targets, or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data is multi-dimensional and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries don’t allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to effortlessly sort and filter plots by categorical or numerical variables. MODE allows users to build and share these displays with several options for plot design and meta selection. In conclusion, the MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

lipidomics↗