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Results of a hardware vs. software correlation of the RDV77 session are presented. Group delays are found to agree (WRMS differences) at an average level of 4.2 psec and with a noise floor of 2.5 psec. These RDV77 comparisons agree well with several previous correlator comparison studies.
Dendritic growth velocities in undercooled melts of pure Ni have been intensively studied over the past fifty years. However, the literature data are at marked variance with the prediction of the widely accepted model for rapid dendritic growth both at small and at large undercoolings. In the present work, bulk melts of pure Ni samples of high purity were undercooled by glass fluxing treatment under a static magnetic field. The recalescence processes of the samples at different undercoolings were recorded using a high-speed camera, and were modeled using a software to determine the dendritic growth velocities. The present data confirmed the effect of melt flow on dendritic growth velocities at undercoolings below 100 K. A comparison of the present data with previous measurements on a lower purity material suggested an effect of impurities on dendritic growth velocities at undercoolings larger than 200 K as well.
The Thermal Control Subsystem (TCS) is a key part of the Advanced Plant Habitat (APH) for the International Space Station (ISS). The purpose of this subsystem is to provide thermal control, mainly cooling, to the other APH subsystems. One of these subsystems, the Environmental Control Subsystem (ECS), controls the temperature and humidity of the growth chamber (GC) air to optimize the growth of plants in the habitat. The TCS provides thermal control to the ECS with three cold plates, which use Thermoelectric Coolers (TECs) to heat or cool water as needed to control the air temperature in the ECS system. In order to optimize the TCS design, pressure drop and heat transfer analyses were needed. The analysis for this system was performed in Siemens NX Thermal/Flow software (Version 8.5). NX Thermal/Flow has the ability to perform 1D or 3D flow solutions. The 1D flow solver can be used to represent simple geometries, such as pipes and tubes. The 1D flow method also has the ability to simulate either fluid only or fluid and wall regions. The 3D flow solver is similar to other Computational Fluid Dynamic (CFD) software. TCS performance was analyzed using both the 1D and 3D solvers. Each method produced different results, which will be evaluated and discussed.
Advances in modeling and simulation, new finite element software, modeling engines and powerful computers are providing opportunities to interrogate designs in a very different manner and in a more detailed approach than ever before. Margins of safety are also often evaluated using local stresses for various design concepts and design parameters quickly once analysis models are defined and developed. This paper suggests that not all the negative margins of safety evaluated are real. The structural areas where negative margins are frequently encountered are often near stress concentrations, point loads and load discontinuities, near locations of stress singularities, in areas having large gradients but with insufficient mesh density, in areas with modeling issues and modeling errors, and in areas with connections and interfaces, in two-dimensional (2D) and three-dimensional (3D) transitions, bolts and bolt modeling, and boundary conditions. Now, more than ever, structural analysts need to examine and interrogate their analysis results and perform basic sanity checks to determine if these negative margins are real.
The goal of this presentation is to provide a general overview of the multi-scale modeling formulation to determine if there is additional surface recession in Thermal Protection Systems (TPS) materials as a result of mechanical erosion due to high shear conditions during atmospheric entry. This modeling process is performed at different scales by leveraging two computational frameworks developed at NASA: the Porous Microstructure Analysis (PuMA) software, and the Porous material Analysis Toolbox based on OpenFOAM (PATO). PuMA specializes in computing effective macro-scale material properties by performing material response simulations on 3D digital micro-scale representations of porous micro-structures. The modeling of TPS materials at the micro-scale is essential to understand how they behave as part of a heat shield assembly. The first part of the presentation will detail the implementation of PuMA’s cell-centered finite volume elasticity solver, which allows the computation of macro-scale effective mechanical properties of heterogeneous and anisotropic materials such as fibrous and woven TPS composites. These homogenized mechanical properties are used by PATO’s mechanical erosion model to predict the TPS material’s recession at a larger scale. This work will also provide some examples of multi-scale analysis from the fiber level up to the unit cell. The second part of the presentation will focus on the macro-scale approach to determine if erosion at the heat shield’s surface occurs due to mechanical and thermal loads experienced during atmospheric entry. To accomplish this, a solid mechanics module was integrated within PATO enabling it to model the potential mechanical erosion in three steps: first, after obtaining the effective mechanical properties with PuMA, the implemented stress analysis solver computes the stress and the displacement fields for the TPS material using the wall shear stress tensor, computed using a CFD solver, as boundary conditions; then, regions on the surface where the stress meets the failure criteria are identified; finally, the failed material is removed and the mesh is redistributed accordingly. The outcome is a model capable of predicting the total recession in the material due to surface chemistry and mechanical erosion.
This is a short architectural note for a critical component of safely scaling drone operations. The primary motivation for this note is to collect language and terminology around the Discovery and Synchronization Service (DSS) as it is currently implemented for Uncrewed Aircraft System (UAS) Traffic Management. The major driver for this document was frequent miscommunication about DSS. Often there have been multiple informed and invested stakeholders in the same room making statements about “multiple DSSs” and each of them meaning something slightly different.
In the past few years, there has been a renewed interest in the deployment of nuclear power for decarbonizing the electricity grid as well as a range of industrial applications. As the demonstrations of advanced nuclear power plants start to begin, there will likely be a further increase in this interest. As nuclear is being considered as a part of the energy mix, understanding the cost of nuclear energy becomes increasingly important for all stakeholders including advanced reactor vendors (for making design decisions and marketing their designs), users of nuclear energy (e.g., to estimate the cost of decarbonization of other industries using nuclear), and government (e.g., in capacity expansion models that are used in framing policy). In this summary, we demonstrate a software tool called ACCERT that is currently being developed with funding from the Systems Analysis and Integration (SA&I) program under the Department of Energy’s Office of Nuclear Energy (DOE NE). ACCERT is a cost estimation and techno-economics tool for nuclear power plant applications that includes a database of (a) cost estimates of various ‘reference’ nuclear power plant designs gathered from existing literature, and (b) algorithms developed from these costs that can be used extrapolate the existing costs and perform a bottom-up cost estimation of other designs. A companion summary describes the software and its design in more detail and this summary presents a demonstration for four different nuclear power plant designs: a pressurized water reactor (PWR), high-temperature gas reactor (HTGR), sodium fast reactor (SFR), and a heat-pipe microreactor. The demonstrations include the reference cost estimates and the cost estimates of a modified design for each reference case.
SAND2022-1525 O The Central Alarm System (CAS) training simulator is a standalone application that will work on any Alarm Control and Display (AC&D) System. Designed to be used by an instructor in a classroom environment, this software plays back scenario alarms and videos usually exported out of Scribe3D or any software that can produce scenario-based videos. Users can select from an array of different scenarios to play. The alarms are sent to an AC&D controller and the videos are sent to a Video Management Server (VMS). Both alarms and associated videos displayed by the intended AC&D system. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
When developing techniques and products for instruction on manned spaceflight systems, training organizations are often faced with two very different customers: ground operators and onboard crewmembers. Frequently, instructional development focuses on one of these customers with the assumption that the other s needs will be met by default. Experience teaches us that differing approaches are required when developing training tailored to the specific needs of each customer. As a rule, ground operators require focused instruction on specific areas of expertise. Their knowledge should be of the details of the hardware, software, and operational techniques associated with that system. They often benefit from historical knowledge of how their system has operated over its lifetime. Since several different ground operators may be interfacing with the same system, each individual operator must understand the agreed-to principles by which that system will be run. In contrast, onboard crewmembers require a more broad, hands-on awareness of their operational environment. Their training should be developed with an understanding of the physical environment in which they live and work and the day-to-day tasks they are most likely to perform. Rarely do they require a deep understanding of the details of a system; it is often sufficient to teach them just enough to maintain situational awareness and perform basic tasks associated with maintenance and operation of onboard systems. Crewmembers may also develop unique onboard operational techniques that differ from preceding crews. They should be taught what flexibility they have in systems operations and how their specific habits can be communicated to ground support personnel. This paper will explore the techniques that can be employed when developing training for these unique customers. We will explore the history of International Space Station training development and how past efforts can guide us in creating training for users of future manned spaceflight efforts.
The outlet temperature targets for Gen 3 Concentrating Solar Power (CSP) systems pose a significant challenge to the structural reliability of high temperature metallic components, including those manufactured from nickel-based superalloys. Advanced ceramics present a potential solution due to their excellent high-temperature strength. However, accurate assessment of ceramic components requires an entirely different approach compared to metallic components. This paper describes the implementation of time-dependent reliability analysis of ceramic components in srlife – an open-source software package for estimating the life of high temperature CSP components. This new capability will allow high temperature CSP designers to make fair comparisons between competing metallic and ceramic designs and accurately assess the performance of different ceramic materials for CSP receivers and other components. The current version of the tool is available at https://github.com/Argonne-National-Laboratory/srlife.
The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM supports the HERON software module in the evaluation of the optimal dispatch by evaluating feasible set-points for the different IES unit components. Set-points are required to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). This problem is addressed by adopting a two-stage approach. First, the HERON power dispatcher determines set-points that meet the constraints on the former variables (e.g., power levels and power ramp rate limits). These constraints are called explicit constraints. Then, FARM adjusts these set-points to ensure the respect of the limits on the latter variables given the knowledge of the system physics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). The original version of the FARM software module (FARM-Alpha) was released by Argonne National Laboratory in January 2021. In the latest version of the code released in July 2022 (FARM-Delta), the Reference Governor (RG) algorithm was upgraded to a Multi-Input Multi-Output version from its original Single-Input Single-Output form. The RG algorithm acts to enforce constraints. With this improvement an IES unit is now treated as a single dynamic system from the standpoint of control. The crosstalk among components in an IES unit is now fully considered thereby ensuring a true optimization is obtained for those units that have multiple set-points. In this report, the capabilities of FARM-Delta operating within the FORCE ecosystem are demonstrated for an IES test case. The specific configuration of IES unit for this case was selected by the IES team with consultation from the Advanced Reactor IES Expert Group. A full TEA analysis that invoked HERON, HYBRID, FARM, and RAVEN was performed and serves to demonstrate how the latest modification to FARM algorithms (i.e., state variable selection, state-space matrices derivation, set-point verification) can shape setpoints that might otherwise compromise the health of equipment through accelerated wear and tear. In this specific test case, it was demonstrated that these algorithms ensure a more efficient utilization of steam resources to be shared by two different subsystems, namely Balance of Plant (BOP) and High-Temperature Steam Electrolysis (HTSE). Finally, some code improvements that can further enhance the user-friendliness are suggested.
A software that delivers parameters from energy storage system (ESS) to container, rack, module and single cell design, as well as data analysis on arbitrage energy and frequency regulation of ESS in different regions, has been developed. The Lithium-ion Battery Design for Grid-scale Energy Storage App V1.0 has the capability to output the system, module and cell design with the energy, power, capacity, group method, cost of single cell, and single cell test protocol which break down from input energy storage system data in different regions. The default chemistry of the battery is LiFePO4 and graphite. The energy density of the graphite/LiFePO 4 pouch cell ranges from 100 Wh/kg to 200 Wh/Kg in the software. Graphite/LiFePO 4 pouch cell (up to 1Ah in lab) manufacturing line is also built and can be used to evaluate the test protocol, moreover, for electrolyte evaluation in other ESMI seedling projects. The software enables rapid prototyping to accelerate energy storage research, development, and manufacturing.
This document describes the relevant equations programmed in spreadsheet software, SepTOOL, developed by ZIN Technologies, Inc. (ZIN) to determine the separation clearance between a launch vehicle payload fairing and remaining stages. The software uses closed form rigid body dynamic solutions of the vehicle in combination with flexible body dynamics of the fairing, which is obtained from flexible body dynamic analysis or from test data, and superimposes the two results to obtain minimum separation clearance for any given set of flight trajectory conditions. Using closed form solutions allows SepTOOL to perform separation calculations several orders of magnitude faster compared to numerical methods which allows users to perform real time parameter studies. Moreover, SepTOOL can optimize vehicle performance to minimize separation clearance. This tool can evaluate various shapes and sizes of fairings along with different vehicle configurations and trajectories. These geometries and parameters are inputted in a user friendly interface. Although the software was specifically developed for evaluating the separation clearance of launch vehicle payload fairings, separation dynamics of other launch vehicle components can be evaluated provided that aerodynamic loads acting on the vehicle during the separation event are negligible. This document describes the development of SepTOOL providing analytical procedure and theoretical equations whose implementation of these equations is not disclosed. Realistic examples are presented, and the results are verified with ADAMS (MSC Software Corporation) simulations. It should be noted that SepTOOL is a preliminary separation clearance assessment software for payload fairings and should not be used for final clearance analysis.
Fundamental to vehicle health management is the deployment of systems incorporating advanced technologies for predicting and detecting anomalous conditions in highly complex and integrated environments. Integrated structural integrity health monitoring, statistical algorithms for detection, estimation, prediction, and fusion, and diagnosis supporting adaptive control are examples of advanced technologies that present considerable verification and validation challenges. These systems necessitate interactions between physical and software-based systems that are highly networked with sensing and actuation subsystems, and incorporate technologies that are, in many respects, different from those employed in civil aviation today. A formidable barrier to deploying these advanced technologies in civil aviation is the lack of enabling verification and validation tools, methods, and technologies. The development of new verification and validation capabilities will not only enable the fielding of advanced vehicle health management systems, but will also provide new assurance capabilities for verification and validation of current generation aviation software which has been implicated in anomalous in-flight behavior. This paper describes the research focused on enabling capabilities for verification and validation underway within NASA s Integrated Vehicle Health Management project, discusses the state of the art of these capabilities, and includes a framework for prioritizing activities.
The development of the Sampling and Caching Subsystem (SCS) of the Mars 2020 Rover Mission is highly dependent on testing of prototype hardware and software operating in explicit conditions as part of integrated testbeds. To achieve relevant integration of hardware and software while maintaining rapid algorithm development capabilities and high testing throughput, the Controls and Autonomy for Sample Acquisition and Handling (CASAH) software system was developed. CASAH is an implementation of the Intelligent Robotics System Architecture (IRSA),which mimics JPL Flight Software (FSW) in that it is divided into hierarchical modules that run separate processes that communicate via message passing, each module is assigned an owner that is a single developer, and the operator initiates requests via a text-based interface that interprets sequences of commands.IRSA enables a modular breakdown of CASAH that follows that of 2020 Flight Software,so developers can take an algorithm from a module in CASAH and re-code it into the same module in FSW. As deployment of CASAH has grown to ten testbeds - each with different hardware and objectives - bottom-up design decisions have been intentionally made to keep the system lightweight and maintainable by a very small team. To date, CASAH has been used to run 1393 different tests. This work describes CASAH, the testbeds and functionality it supports, the tools used to manage the development and sharing of code, and the features of the software. Lessons learned over the past three years of development and deployment are provided.
Three well-characterized heme peroxidases (cytochrome c peroxidase = CCP, ascorbate peroxidase = APX, and Leishmania major peroxidase = LMP) all have a Trp residue tucked under the heme stacked against the proximal His heme ligand. The reaction of peroxidases with H 2 O 2 to give Compound I results in the oxidation of this Trp to a cationic radical in CCP and LMP but not in APX. Considerable experimental data indicate that the local electrostatic environment controls whether this Trp or the porphyrin is oxidized in Compound I. Attempts have been made to place the differences between these peroxidases on a quantitative basis using computational methods. These efforts have been somewhat limited by the approximations required owing to the computational cost of using fully solvated atomistic models with well-developed forcefields. This now has changed with available GPU computing power and the associated development of software. Here we employ thermodynamic integration and multistate Bennett acceptance ratio methods to help fine-tune our understanding on the energetic differences in Trp radical stabilization in all three peroxidases. These results indicate that the local solvent structure near the redox active Trp plays a significant role in stabilization of the cationic Trp radical.
The fact that Deterministic Design Method no longer satisfies most design needs calls for methods that will cope with the high trend in technology. The advance in computer technology has reduced the rigors that normally accompany many design analysis methods that account for uncertainties in design parameters. Probabilistic Design Methodology (PDM) is beginning to make impact in engineering design. This method is gaining more recognition in industries than in educational institutions. Some of the reasons for the limited use of the PDM at the moment are that many are unaware of its potentials, and most of the software developed for PDM are very recent. The central goal of the PDM project at Tennessee State University is to introduce engineering students to this method. The students participating in the project learn about PDM and the computer codes that are available to the design engineer. The software being used for this project is NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) developed under NASA probabilistic structural analysis program. NESSUS has three different modules which make it a very comprehensive computer code for PDM. Since this method is new to the students, its introduction into the engineering curriculum is to be in stages. These range from the introduction of PDM and its software to the applications. While this program is being developed for its eventual inclusion into the engineering curriculum, some graduate and undergraduate students are already carrying out some projects using this method. As the students are increasing their understanding on PDM, they are at the same time applying it to some common design problems. The areas this method is being applied at the moment include, Design of Gears (spur and worm); Design of Brakes; Design of Heat Exchangers Design of Helical Springs; and Design of Shock Absorbers. Some of the current results of these projects are presented.
Wing-Viewer is a computer program for acquisition and reduction of image data acquired by any of five different scientificgrade commercial electronic cameras used at Langley Research center to observe wind-tunnel models coated with pressure or temperature-sensitive paints (PSP/TSP). Wing-Viewer provides full automation of camera operation and acquisition of image data, and has limited data-preprocessing capability for quick viewing of the results of PSP/TSP test images. Wing- Viewer satisfies a requirement for a standard interface between all the cameras and a single personal computer: Written by use of Microsoft Visual C++ and the Microsoft Foundation Class Library as a framework, Wing-Viewer has the ability to communicate with the C/C++ software libraries that run on the controller circuit cards of all five cameras.