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At least 1,495 records · Page 83

Rapid Geometry Creation for Computer-Aided Engineering Parametric Analyses: A Case Study Using ComGeom2 for Launch Abort System Design

ComGeom2, a tool developed to generate Common Geometry representation for multidisciplinary analysis, has been used to create a large set of geometries for use in a design study requiring analysis by two computational codes. This paper describes the process used to generate the large number of configurations and suggests ways to further automate the process and make it more efficient for future studies. The design geometry for this study is the launch abort system of the NASA Crew Launch Vehicle.

Hawke, Veronica↗

Chimera Grid Tools

Chimera Grid Tools (CGT) is a software package for performing computational fluid dynamics (CFD) analysis utilizing the Chimera-overset-grid method. For modeling flows with viscosity about geometrically complex bodies in relative motion, the Chimera-overset-grid method is among the most computationally cost-effective methods for obtaining accurate aerodynamic results. CGT contains a large collection of tools for generating overset grids, preparing inputs for computer programs that solve equations of flow on the grids, and post-processing of flow-solution data. The tools in CGT include grid editing tools, surface-grid-generation tools, volume-grid-generation tools, utility scripts, configuration scripts, and tools for post-processing (including generation of animated images of flows and calculating forces and moments exerted on affected bodies). One of the tools, denoted OVERGRID, is a graphical user interface (GUI) that serves to visualize the grids and flow solutions and provides central access to many other tools. The GUI facilitates the generation of grids for a new flow-field configuration. Scripts that follow the grid generation process can then be constructed to mostly automate grid generation for similar configurations. CGT is designed for use in conjunction with a computer-aided-design program that provides the geometry description of the bodies, and a flow-solver program.

Chan, William M.↗

Enabling Future Robotic Missions with Multicore Processors

Recent commercial developments in multicore processors (e.g. Tilera, Clearspeed, HyperX) have provided an option for high performance embedded computing that rivals the performance attainable with FPGA-based reconfigurable computing architectures. Furthermore, these processors offer more straightforward and streamlined application development by allowing the use of conventional programming languages and software tools in lieu of hardware design languages such as VHDL and Verilog. With these advantages, multicore processors can significantly enhance the capabilities of future robotic space missions. This paper will discuss these benefits, along with onboard processing applications where multicore processing can offer advantages over existing or competing approaches. This paper will also discuss the key artchitecural features of current commercial multicore processors. In comparison to the current art, the features and advancements necessary for spaceflight multicore processors will be identified. These include power reduction, radiation hardening, inherent fault tolerance, and support for common spacecraft bus interfaces. Lastly, this paper will explore how multicore processors might evolve with advances in electronics technology and how avionics architectures might evolve once multicore processors are inserted into NASA robotic spacecraft.

multi-core processor↗

Coring Sample Acquisition Tool

A sample acquisition tool (SAT) has been developed that can be used autonomously to sample drill and capture rock cores. The tool is designed to accommodate core transfer using a sample tube to the IMSAH (integrated Mars sample acquisition and handling) SHEC (sample handling, encapsulation, and containerization) without ever touching the pristine core sample in the transfer process.

Haddad, Nicolas E.↗

NASA's Space Launch System Program Update

Hardware and software for the world's most powerful launch vehicle for exploration is being welded, assembled, and tested today in high bays, clean rooms and test stands across the United States. NASA's Space Launch System (SLS) continued to make significant progress in 2014 with more planned for 2015, including firing tests of both main propulsion elements and the program Critical Design Review (CDR). Developed with the goals of safety, affordability, and sustainability, SLS will still deliver unmatched capability for human and robotic exploration. The initial Block 1 configuration will deliver more than 70 metric tons of payload to low Earth orbit (LEO). The evolved Block 2 design will deliver some 130 metric tons to LEO. Both designs offer enormous opportunity and flexibility for larger payloads, simplifying payload design as well as ground and on-orbit operations, shortening interplanetary transit times, and decreasing overall mission risk. Over the past year, every vehicle element has manufactured or tested hardware. An RS-25 liquid propellant engine was hotfire-tested at NASA's Stennis Space Center, Miss. for the first time since 2009 exercising and validating the new engine controller, the renovated A-1 test stand, and the test teams. Four RS-25s will power the SLS core stage. A qualification five-segment solid rocket motor incorporating several design, material, and process changes was scheduled to be test-fired in March at the prime contractor's facility in Utah. The booster also successfully completed its Critical Design Review (CDR) validating the planned design. All six major manufacturing tools for the core stage are in place at the Michoud Assembly Facility in Louisiana, and have been used to build numerous pieces of confidence, qualification, and even flight hardware, including barrel sections, domes and rings used to assemble the world's largest rocket stage. SLS Systems Engineering accomplished several key tasks including vehicle avionics software and hardware build and testing, scale model acoustic and base heating tests. Construction of the Interim Cryogenic Propulsion Stage (ICPS) began. Advanced development provided a look into the future of SLS. Shell buckling knockdown factor testing refined decades-old design margins that added thousands of pounds to rocket payloads. Adaptive manufacturing and structured light scanning development promised to cut the cost and time associated with manufacturing and testing. This paper will provide an overview of the progress made over the past year and provide a glimpse of 2015 milestones and beyond on the way to the first launch in 2018.

May, Todd↗

NASA's Space Launch System Program Update

Hardware and software for the world's most powerful launch vehicle for exploration is being welded, assembled, and tested today in high bays, clean rooms and test stands across the United States. NASA's Space Launch System (SLS) continued to make significant progress in 2014 with more planned for 2015, including firing tests of both main propulsion elements and the program Critical Design Review (CDR). Developed with the goals of safety, affordability, and sustainability, SLS will still deliver unmatched capability for human and robotic exploration. The initial Block 1 configuration will deliver more than 70 metric tons of payload to low Earth orbit (LEO). The evolved Block 2 design will deliver some 130 metric tons to LEO. Both designs offer enormous opportunity and flexibility for larger payloads, simplifying payload design as well as ground and on-orbit operations, shortening interplanetary transit times, and decreasing overall mission risk. Over the past year, every vehicle element has manufactured or tested hardware. An RS-25 liquid propellant engine was hotfire-tested at NASA's Stennis Space Center, Miss. for the first time since 2009 exercising and validating the new engine controller, the renovated A-1 test stand, and the test teams. Four RS-25s will power the SLS core stage. A qualification five-segment solid rocket motor incorporating several design, material, and process changes was scheduled to be test-fired in March at the prime contractor's facility in Utah. The booster also successfully completed its Critical Design Review (CDR) validating the planned design. All six major manufacturing tools for the core stage are in place at the Michoud Assembly Facility in Louisiana, and have been used to build numerous pieces of confidence, qualification, and even flight hardware, including barrel sections, domes and rings used to assemble the world's largest rocket stage. SLS Systems Engineering accomplished several key tasks including vehicle avionics software and hardware build and testing, scale model acoustic and base heating tests. Construction of the Interim Cryogenic Propulsion Stage (ICPS) began. Advanced development provided a look into the future of SLS. Shell buckling knockdown factor testing refined decades-old design margins that added thousands of pounds to rocket payloads. Adaptive manufacturing and structured light scanning development promised to cut the cost and time associated with manufacturing and testing. This paper will provide an overview of the progress made over the past year and provide a glimpse of 2015 milestones and beyond on the way to the first launch in 2018.

May, Todd↗

SLS Flight Software Testing: Using a Modified Agile Software Testing Approach

NASA's Space Launch System (SLS) is an advanced launch vehicle for a new era of exploration beyond earth's orbit (BEO). The world's most powerful rocket, SLS, will launch crews of up to four astronauts in the agency's Orion spacecraft on missions to explore multiple deep-space destinations. Boeing is developing the SLS core stage, including the avionics that will control vehicle during flight. The core stage will be built at NASA's Michoud Assembly Facility (MAF) in New Orleans, LA using state-of-the-art manufacturing equipment. At the same time, the rocket's avionics computer software is being developed here at Marshall Space Flight Center in Huntsville, AL. At Marshall, the Flight and Ground Software division provides comprehensive engineering expertise for development of flight and ground software. Within that division, the Software Systems Engineering Branch's test and verification (T&V) team uses an agile test approach in testing and verification of software. The agile software test method opens the door for regular short sprint release cycles. The idea or basic premise behind the concept of agile software development and testing is that it is iterative and developed incrementally. Agile testing has an iterative development methodology where requirements and solutions evolve through collaboration between cross-functional teams. With testing and development done incrementally, this allows for increased features and enhanced value for releases. This value can be seen throughout the T&V team processes that are documented in various work instructions within the branch. The T&V team produces procedural test results at a higher rate, resolves issues found in software with designers at an earlier stage versus at a later release, and team members gain increased knowledge of the system architecture by interfacing with designers. SLS Flight Software teams want to continue uncovering better ways of developing software in an efficient and project beneficial manner. Through agile testing, there has been increased value through individuals and interactions over processes and tools, improved customer collaboration, and improved responsiveness to changes through controlled planning. The presentation will describe agile testing methodology as taken with the SLS FSW Test and Verification team at Marshall Space Flight Center.

Bolton, Albanie T.↗

Analysis of Sample Acquisition Dynamics Using Discrete Element Method

The analysis presented in this paper is conducted in the framework of the Ocean Worlds Autonomy Testbed for Exploration Research and Simulation (OceanWATERS) project, currently under development at NASA Ames Research Center. OceanWATERS aims at designing a simulation environment which allows for testing autonomy of scientific lander missions to the icy moons of our solar system. Mainly focused on reproducing the end effector interaction with the inherent terrain, this paper introduces a novel discrete element method (DEM)-based approach to determine forces and torques acting on the lander’s scoop during the sample acquisition process. An accurate force feedback from the terrain on the scoop is required by fault-detection and autonomous decision-making algorithms to identify when the requested torque on the robotic arm’s joints exceeds the maximum available torque. Knowledge of the terrain force feedback significantly helps evaluating the arm’s links structural properties and properly selecting actuators for the joints. Models available in literature constitute a partial representation of the dynamics of the interaction. As an example, Balovnev derived an analytical expression of the vertical and horizontal force acting on a bucket while collecting a sample as a function of its geometry and velocity, soil parameters and reached depth. Although the model represents an adequate approximation of the two force components, it ignores the direction orthogonal to the scoop motion and neglects the torque. This work relies on DEM analysis to compensate for analytical models’ deficiencies and inaccuracies, i. e. provide force and torque 3D vectors, defined in the moving reference (body) frame attached to the scoop, at each instant of the sample collection process. Results from the first presented analysis relate to the specific OceanWATERS sampling strategy, which consists of collecting the sample through five consecutive passes with increasing depth, each pass following the same circularlinear- circular trajectory. Data is collected given a specific scoop design interacting with two types of bulk materials, which may characterize the surface of icy planetary bodies: snow and ice. Although specifically concerned with the OceanWATERS design, this first analysis provides the expected force trends for similar sampling strategies and allows to deduce phenomenological information about the general scooping process. In order to further instruct the community on the use of DEM tools as a solution to the sampling collection problem, two more analyses have been carried out, mainly focused on reducing the DEM computation time, which increases with a decrease in particle size. After running a set of identical simulations, where the only changing parameter is the size of the spherical particle, it is observed that the resulting force trajectories, starting from a given particle size, converge to the true trend. It is deducible that a further decrease in size yields negligible improvements in the accuracy, while it sensibly increases computation time. A final analysis aims at discussing limitations of approximating bulk material particles having a complex shape, e. g. ice fragments, with spheres, by comparing force trends resulting in the two cases for the same simulation scenario.

Catanoso, Damiana↗

Evaluating Lunar Water Processing System Model Configurations for Small Scale Oxygen and Hydrogen Production Within JAXA'S ISRU Technology

Introduction: In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s) range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant. System Model: In FY24, the System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team developed a lunar water processing system model using the Mission Analysis and Integration Tool (MAIT) to estimate the M/V/P for ISRU subsystems operating under a wide range of Hydrogen (H2) and Oxygen (O2) production targets for the Space Technology Mission Directorate (STMD) [1]. Based on Japan Aerospace Exploration Agency’s (JAXA) surface operational requirements, this system architecture was modified to include the ability to excavate consolidated icy regolith (versus granular ice excavation using Kennedy Space Center’s (KSC) ISRU Pilot Excavator, IPEx) and explore the feasibility of processing the lunar water both inside and outside of the PSR. For the consolidated icy regolith case study, excavation was performed via a mobility transport chassis outfitted with The Regolith Ice Drill for Exploring New Terrain (TRIDENT) for drilling [2] and the Cold Operable Lunar Deployable Arm (COLDArm) [3] for regolith transfer. The system model determines the required rover and payload. M/V/P to handle the required regolith processing rates. The regolith is then sorted and heated to sublimate the ice (via an auger dryer). The exiting high temperature, low pressure vapor is cleaned of volatiles (via cold trap) and electrolyzed to produce H2 and O2. These products are then dried, liquified with 20 K and 90 K cryocoolers (for H2 and O2, respectively), and stored in cylindrical tanks. Study Goals: Due to the different ConOps options of regolith transport to the ridge for processing versus processing it directly inside the PSR, as well as the unknown regolith/water-ice composition, new excavation techniques and their power configurations are being evaluated within a ISRU system architecture for production targets less than NASA’s pilot plant (1 mT). This analysis investigates the feasibility of numerous excavation techniques, power architectures, and logistical operations and determines an optimal system configuration with regards to M/V/P. It aims to investigate which parameters, both locally and globally, have the greatest effect on each subsystem within the plant. This can be used to identify the most critical components of the plant, and guide future decisions on allocating funding for research and development. The results from this study may provide subsystem developers with appropriate interfaces with excavation subsystems and downstream processes, and assessing the overall feasibility of each excavation technique, power architecture, and logistical timeframe. References: [1] Carlson, A. et. al. (2024) ICES. [2] Zacny, K., et. al. (2024) “ASCE Earth and Space”. [3] McCormick, R., et. Al. (2024) IEEE Xplore.

ISRU↗

Analytical Framework for Homeowner-Focused Computational Cost-Benefit Mitigation Decision Making

As a result of increasing windstorm losses in the United States over the past 50 years, a variety of residential wind hazard mitigation strategies have been recommended. Wind hazard mitigation undoubtedly reduces windstorm losses; however, little customized information is available to support the economic decision-making process for individual stakeholders, especially at the consumer level. Therefore, there is a need for decision support tools to calculate, evaluate, and present the economic benefits of mitigation over variable decision-making time horizons for unique building characteristics in specific geographical locations. This paper presents a cost-benefit computational decision-making recommendation framework that evaluates and presents the cost effectiveness of mitigation, customized based on location, years of interest, and building characteristics. The decision-making framework consists of two cores. The user-independent core and user-dependent core which consists of eight steps, divided into four subprocesses: (1) data acquisition, (2) data evaluation, (3) cost-benefit calculation, and (4) results comparison and decision making. To demonstrate the framework, a wood-framed single-family home in light suburban terrain in Golden Meadow, Louisiana, is used as a case study, considering retrofit mitigation with a $15,000 budget and a decision-making time horizon of 30 years. The case study provides six mitigation options, with cost ranging between approximately $2,000 and $15,000 and net benefit/cost ratios ranging from 2.4 to 13. Once fully implemented in a decision making information tool, the developed mitigation recommendation framework will provide valuable information that can be used by home designers, builders, owners, and other stakeholders to better understand the economic facets of wind hazard mitigation, providing critical information as part of the overall decision-making process.

Orooji, Fatemeh↗

On the next generation of reliability analysis tools

The current generation of reliability analysis tools concentrates on improving the efficiency of the description and solution of the fault-handling processes and providing a solution algorithm for the full system model. The tools have improved user efficiency in these areas to the extent that the problem of constructing the fault-occurrence model is now the major analysis bottleneck. For the next generation of reliability tools, it is proposed that techniques be developed to improve the efficiency of the fault-occurrence model generation and input. Further, the goal is to provide an environment permitting a user to provide a top-down design description of the system from which a Markov reliability model is automatically constructed. Thus, the user is relieved of the tedious and error-prone process of model construction, permitting an efficient exploration of the design space, and an independent validation of the system's operation is obtained. An additional benefit of automating the model construction process is the opportunity to reduce the specialized knowledge required. Hence, the user need only be an expert in the system he is analyzing; the expertise in reliability analysis techniques is supplied.

Babcock, Philip S., IV↗

The GGCMI Phase 2 Experiment: Global Gridded Crop Model Simulations Under Uniform Changes in CO2, Temperature, Water, and Nitrogen Levels (Protocol Version 1.0)

Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.

GGCMI↗

Developing a Logistics Data Process for Support Equipment for NASA Ground Operations

The United States NASA Space Shuttle has long been considered an extremely capable yet relatively expensive rocket. A great part of the roughly US $500 million per launch expense was the support footprint: refurbishment and maintenance of the space shuttle system, together with the long list of resources required to support it, including personnel, tools, facilities, transport and support equipment. NASA determined to make its next rocket system with a smaller logistics footprint, and thereby more cost-effective and quicker turnaround. The logical solution was to adopt a standard Logistics Support Analysis (LSA) process based on GEIA-STD-0007 http://www.logisticsengineers.org/may09pres/GEIASTD0007DEXShortIntro.pdf which is the successor of MIL-STD-1388-2B widely used by U.S., NATO, and other world military services and industries. This approach is unprecedented at NASA: it is the first time a major program of programs, Project Constellation, is factoring logistics and supportability into design at many levels. This paper will focus on one of those levels NASA ground support equipment for the next generation of NASA rockets and on building a Logistics Support Analysis Record (LSAR) for developing and documenting a support solution and inventory of resources for. This LSAR is actually a standards-based database, containing analyses of the time and tools, personnel, facilities and support equipment required to assemble and integrate the stages and umbilicals of a rocket. This paper will cover building this database from scratch: including creating and importing a hierarchical bill of materials (BOM) from legacy data; identifying line-replaceable units (LRUs) of a given piece of equipment; analyzing reliability and maintainability of said LRUs; and therefore making an assessment back to design whether the support solution for a piece of equipment is too much work, i.e., too resource-intensive. If one must replace or inspect an LRU too much, perhaps a modification of the design of the equipment can make such operational effort unnecessary. Finally, this paper addresses processes of tying resources to a timeline of tasks performed in ground operations: this enables various overarching analyses, e.g., a summarization of all resources used for a given piece of equipment. Quality Control of data will also be discussed: importing and exporting data from product teams, including spreadsheets-todatabase or data exchange between databases.

Chakrabarti, Suman↗

Improvement of Automated POST Case Success Rate Using Support Vector Machines

During early conceptual design of complex systems, concept down selection can have a large impact upon program life-cycle cost. Therefore, any concepts selected during early design will inherently commit program costs and affect the overall probability of program success. For this reason it is important to consider as large a design space as possible in order to better inform the down selection process. For conceptual design of launch vehicles, trajectory analysis and optimization often presents the largest obstacle to evaluating large trade spaces. This is due to the sensitivity of the trajectory discipline to changes in all other aspects of the vehicle design. Small deltas in the performance of other subsystems can result in relatively large fluctuations in the ascent trajectory because the solution space is non-linear and multi-modal [1]. In order to help capture large design spaces for new launch vehicles, the authors have performed previous work seeking to automate the execution of the industry standard tool, Program to Optimize Simulated Trajectories (POST). This work initially focused on implementation of analyst heuristics to enable closure of cases in an automated fashion, with the goal of applying the concepts of design of experiments (DOE) and surrogate modeling to enable near instantaneous throughput of vehicle cases [2]. Additional work was then completed to improve the DOE process by utilizing a graph theory based approach to connect similar design points [3]. The conclusion of the previous work illustrated the utility of the graph theory approach for completing a DOE through POST. However, this approach was still dependent upon the use of random repetitions to generate seed points for the graph. As noted in [3], only 8% of these random repetitions resulted in converged trajectories. This ultimately affects the ability of the random reps method to confidently approach the global optima for a given vehicle case in a reasonable amount of time. With only an 8% pass rate, tens or hundreds of thousands of reps may be needed to be confident that the best repetition is at least close to the global optima. However, typical design study time constraints require that fewer repetitions be attempted, sometimes resulting in seed points that have only a handful of successful completions. If a small number of successful repetitions are used to generate a seed point, the graph method may inherit some inaccuracies as it chains DOE cases from the non-global-optimal seed points. This creates inherent noise in the graph data, which can limit the accuracy of the resulting surrogate models. For this reason, the goal of this work is to improve the seed point generation method and ultimately the accuracy of the resulting POST surrogate model. The work focuses on increasing the case pass rate for seed point generation.

Zwack, Matthew R.↗

F-15B QuietSpike(TradeMark) Aeroservoelastic Flight Test Data Analysis

System identification or mathematical modelling is utilised in the aerospace community for the development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. The reason for utilising a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance for the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data for several flight conditions (Mach number) that (i) linear models are inefficient for modelling aeroservoelastic data, (ii) nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data and (iii) the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗

Production of Renewable Natural Gas from Waste Carbon Dioxide Sources (CRADA Final Report)

This CRADA provides new funding from SoCalGas and DOE's BETO and FCTO Offices focused hydrogen mass transfer limitations in H2@Scale processes. The project leverages the existing hydrogen production capabilities at the Energy Systems Integration Facility (ESIF) and SoCalGas' 700 L bioreactor system designed, built, and delivered to NLR under the first phase of this CRADA. This Joint Work Statement will cover new hardware modifications between NLR's electorlyzer stack and the SoCalGas bioreactor located outdoors. The new hardware and controls will provide researchers with the tools needed to obtain preliminary experimental data for a non-provisional application due in July 2019. The IP being developed is expected to improve the productivity of the bioreactor and would have wider impacts on other end-use processes using pressurized hydrogen (H2). In addition, this new funding enhances an existing BETO Biopower award by developing a 10-15 kW electrolyzer that is scalable to the MW-class with reduced capital cost and higher efficiency aimed at improving H2 mass transfer to downstream processes, like biomethanation. Finally due to the close-coupling between the electrolyzer stack and bioreactor, R&D will focus on cell retention, nutrient maintenance, optimal water management and process controls.

08 HYDROGEN↗

Effect of Volumetric Energy Density on Microstructure and Properties of Grade 300 Maraging Steel Fabricated by Laser Powder Bed Fusion

Here this study investigated the effect of laser powder bed fusion process parameters on the microstructure and properties of maraging steel. The results show that the process parameters can be finetuned to achieve both a high build rate/low hardness and low build rate/high hardness during fabrication, enabling the co-design of components where property gradients are desirable such as an injection molding tool where surface hardness is desired to be higher than the bulk, which needs to have higher fracture toughness.

36 MATERIALS SCIENCE↗

On Residual Stresses and Reference Temperatures in Thermomechanical Simulations of Photovoltaic Modules Using the Finite Element Method

Thermomechanical simulation of photovoltaic (PV) modules using the finite element method (FEM) is a useful tool to evaluate module design features in terms of structural integrity, reliability, and durability. One of the main challenges in the numerical modeling of a PV module is the incorporation of residual stresses induced by the manufacturing process. Modeling assumptions and abstractions are necessary to limit the model complexity and reduce the computational time. However, oversimplifications and incorrect assumptions can lead to erroneous numerical results. Unfortunately, much simulation work still neglects process-induced stresses. This can lead to incorrect predictions of the stress-strain history and erroneous conclusions during the design process. In this work, we review current modeling practices for incorporating process-induced stresses, and contrast numerical models that consider residual stresses with those that neglect them. We find that the simulation objective and available material properties dictate which process steps need to be modeled, and explore in depth the modeling of residual stresses induced by the lamination process. We demonstrate that a simplified cooldown procedure at the beginning of the simulation can increase the model accuracy and discuss appropriate choices for starting and reference temperatures in the finite element model.

14 SOLAR ENERGY↗