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Contents include the following: PCB design with HDL designer, design process and schematic capture - symbols and diagrams: 1. Motivation: time savings, money savings, simplicity. 2. Approach: use single tool PCB for FPGA design, more FPGA designs than PCB designers. 3. Use HDL designer for schematic capture.
In the search to bridge current gaps in surveillance and communication technologies, a new type of, aircraft is currently undergoing design. The idea of a High Altitude Long Endurance (HALE) aircraft is already a few decades old, but has only recently become realizable. A relay and collector of information at altitudes of 65,000 feet and higher could greatly improve standards of data exchange, homeland security, and research of the air, land and sea. NASA, as a major force in propulsion research, is exploring methods of powering an autonomous aircraft for days, weeks, or even months without refueling. Such a task requires not only high energy density, but also the ability to make use of renewable energy sources to regenerate power. Hydrogen is one of the most energy dense fuels available. Fuel cells make use of hydrogen by harnessing the energy released as it combines with oxygen to produce electricity and water. Fuel cells are envisioned to occupy future propulsion systems in cooperation with solar cells where the photovoltaic arrays harness sunlight into power which can electrolize the water byproduct into reusable hydrogen and oxygen. Modeling this type of system requires adequate assumptions of support hardware and daily transients in operation. The performance of a regenerative fuel cell propulsion system lies in the flight characteristics (altitude, density, temperature, latitude, etc.). Each subsystem is defined by many parameters which can be varied across wide ranges. Statistical and probabilistic analyses bring forward a wealth of information that can be utilized in the design process. This is necessary since the required technologies are relatively young and barely, if yet, capable. Once the modeling is complete, a design space exploration of this highly constrained scenario can be utilized to find the optimal design. The model will become an interactive environment with which experiments and tests can be run. When linked
Algorithms for rapid generation of moderate-fidelity structural finite element models of air vehicle structures to allow more accurate weight estimation earlier in the vehicle design process have been developed. Application of these algorithms should help to rapidly assess many structural layouts before the start of the preliminary design phase and eliminate weight penalties imposed when actual structure weights exceed those estimated during conceptual design. By defining the structural topology in a fully parametric manner, the structure can be mapped to arbitrary vehicle configurations being considered during conceptual design optimization. Recent enhancements to this approach include the porting of the algorithms to a platform-independent software language Python, and modifications to specifically consider morphing aircraft-type configurations. Two sample cases which illustrate these recent developments are presented.
Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space A dministration Dryden Flight Research Center to automate analysis and design process by leveraging existing tools such as NASTRAN, ZAERO a nd CFD codes to enable true multidisciplinary optimization in the pr eliminary design stage of subsonic, transonic, supersonic, and hypers onic aircraft. This is a promising technology, but faces many challe nges in large-scale, real-world application. This paper describes cur rent approaches, recent results, and challenges for MDAO as demonstr ated by our experience with the Ikhana fire pod design.
In 2017, after 20 years, NASA issued a major revision of its reliability and maintainability (R&M) policy, NASA-STD- 8729.1A. Formerly NASA required certain specific R&M activities during each succeeding phase of project development. Now NASA requires a project to start by including the initial development of R&M requirements and the devising of strategies to implement and verify them. Rather than resolving all the requirements first and then designing the system, as has been usual in systems design, the design process now is to work top down by layers. It begins by first identifying the top level requirements and suggesting top level design strategies for those, then making these higher strategies the basis for a lower level set of requirements, and so on down to the lowest components. This approach is intended to ensure that R&M is designed in from the beginning rather than added later with difficulty to a completed design concept. The new R&M standard uses an innovative and effective top-down system design approach intended to effectively implement R&M.
In 2017, after 20 years, NASA issued a major revision of its reliability and maintainability (R&M) policy, NASA-STD-8729.1A [1]. Formerly NASA required certain specific R&M activities during each succeeding phase of project development. Now NASA requires a project to start by including the initial development of R&M requirements and the devising of strategies to implement and verify them. Rather than resolving all the requirements first and then designing the system, as has been usual in systems design, the design process now is to work top down by layers. It begins by first identifying the top level requirements and suggesting top level design strategies for those, then making these higher strategies the basis for a lower level set of requirements, and so on down to the lowest components. This approach is intended to ensure that R&M is designed in from the beginning rather than added later with difficulty to a completed design concept. The new R&M standard uses an innovative and effective top-down system design approach intended to effectively implement R&M.
Conceptual designs of the propulsor modules for the SUSAN electro-fan aircraft are sought after. Shaft power requirement is reduced by using boundary layer ingesting propulsion technology. There are several obstacles to designing feasible BLI propulsion systems such as inlet distortion, flow blockage from ingesting low-momentum flow, strong coupling between airframe and propulsion systems. Thus, the high fidelity CFD tool is indispensable to assess the performance of the propulsion systems and evaluate the inlet profiles during the design process. Consequently, the CFD data is used to update the inputs for the NPSS model from the initial stage of the system design. Hence, the inlet sizing, fan design, and estimation of the power saving are carried out. Various installation concepts of the mail-slot nacelle, such as under-/over-wing and trailing edge configurations, are investigated for the wing-mounted turbo-electric distributed propulsor module, and their power-saving is evaluated. As for the tail-mounted turbofan engine, the fan diameter and inlet captured area is determined based on the CFD profiles. An appropriate area ratio of the bypass and core ducts is derived from meeting the target bypass ratio from the system design. The baseline fan stage is analyzed by full annulus URANS CFD to assess the efficiency penalty due to the ingested pressure and swirl distortions.
Conceptual designs of the propulsor modules for the SUSAN electro-fan aircraft are sought after. Shaft power requirement is reduced by using boundary layer ingesting propulsion technology. There are several obstacles to designing feasible BLI propulsion systems such as inlet distortion, flow blockage from ingesting low-momentum flow, strong coupling between airframe and propulsion systems. Thus, the high fidelity CFD tool is indispensable to assess the performance of the propulsion systems and evaluate the inlet profiles during the design process. Consequently, the CFD data is used to update the inputs for the NPSS model from the initial stage of the system design. Hence, the inlet sizing, fan design, and estimation of the power saving are carried out. Various installation concepts of the mail-slot nacelle, such as under-/over-wing and trailing edge configurations, are investigated for the wing-mounted turbo-electric distributed propulsor module, and their power-saving is evaluated. As for the tail-mounted turbofan engine, the fan diameter and inlet captured area is determined based on the CFD profiles. An appropriate area ratio of the bypass and core ducts is derived from meeting the target bypass ratio from the system design. The baseline fan stage is analyzed by full annulus URANS CFD to assess the efficiency penalty due to the ingested pressure and swirl distortions.
The Transformational Challenge Reactor (TCR) program is demonstrating an agile development approach to advanced nuclear reactor design, which has traditionally utilized a linear design process. In leveraging artificial intelligence, additive manufacturing, advanced materials, and cutting-edge modeling and simulation, the TCR program aims to minimize the high cost and lengthy deployment timelines now standard in the nuclear industry. Within a relatively short period of time, a robust and mature advanced gas-cooled reactor was iteratively designed under the TCR program, using these cutting-edge technologies. The TCR is a 3 MWt gas-cooled microreactor fueled with uranium nitride (UN) tristructural isotropic (TRISO) fuel particles. Though manufactured via traditional means, these UN TRISO particles are loaded into additively manufactured silicon carbide (SiC) cans [4]. Once loaded with TRISO particles, the SiC cans are densified using a chemical vapor infiltration process. The additively manufactured SiC enables significantly more freedom in the design of the fuel form than could ever be achieved using traditionally manufactured SiC. The helium coolant, pressurized to 5 MPa, enters the core at 300°C and nominally exits it at 500°C. Typically, the most thermally limiting components in any reactor design are the fuel assemblies in the core center. To provide a wide thermal margin in these central fuel assemblies, the flow may be biased toward the center of the core to more effectively cool these fuel assemblies with more power deposition and flatten the core’s radial temperature distribution. An analytical fluid model of the TCR core was developed to explore methods for biasing the flow away from the cooler outer fuel assemblies and towards the hotter inner ones. Higher-fidelity models developed in STAR-CCM+ 2020.3.1, a computational fluid dynamics code, were then utilized to verify the analytical model’s findings.
Managing and referencing design knowledge is a critical activity in the design process. However, reliably retrieving useful knowledge can be a frustrating experience for users of knowledge management systems due to inherent limitations of standard keyword-based searches. In this research, we consider the task of retrieving relevant lessons learned from the NASA Lessons Learned Information System (LLIS). To this end, we apply a state-of-the-art natural language processing (NLP) technique for information retrieval (IR): semantic search with sentence-BERT, which is a modification of a Bidirectional Encoder Representations from Transformers (BERT) model that uses siamese and triplet network architectures to obtain semantically meaningful sentence embeddings. While the pre-trained sBERT model performs well out-of-the-box, we further fine-tune the model on data from the LLIS so that it learns on design engineering-relevant vocabulary. We quantify the improvement in query results using both standard sBERT and fine-tuned sBERT over a keyword search. Our use case throughout the paper is to use queries related to specific requirements from a NASA project. Fine tuning the sBERT model on LLIS data yields a mean average precision (MAP) of 0.807 on queries based on information needs from a real NASA project. Results indicate that applying state-of-the-art natural language processing techniques, especially when finetuned using engineering data, to design information retrieval tasks shows significant promise in modernizing design knowledge management systems.
Human rating begins with design. Converging on the requirements and identifying the risks as early as possible in the design process is essential. Understanding of the interaction between the recovery system and the spacecraft will in large part dictate the achievable reliability of the final design. Component and complete system full-scale flight testing is critical to assure a realistic evaluation of the performance and reliability of the parachute system. However, because testing is so often difficult and expensive, comprehensive analysis of test results and correlation to accurate modeling completes the human rating process. The National Aeronautics and Space Administration (NASA) Orion program uses parachutes to stabilize and decelerate the Crew Exploration Vehicle (CEV) spacecraft during subsonic flight in order to deliver a safe water landing. This paper describes the approach that CEV Parachute Assembly System (CPAS) will take to human rate the parachute recovery system for the CEV.
The results of process characterization, circuit design, and reliability studies for the development of a quad OP amplifier intended for use up to 300 C are presented. A dielectrically isolated complementary vertical bipolar process was chosen to fabricate the amplifier in order to eliminate isolation leakage and the possibility of latch up. Characterization of NPN and PNP junctions showed them to be suitable for use up to 300 C. Interconnect reliability was predicted to be greater than four years mean time between failure. Parasitic MOS formation was eliminated by isolation of each device.
Due to the dilute nature of products manufactured via fermentation and cell-free bioprocessing, dewatering is a common unit operation in downstream processing (DSP) for bioproduct recovery, but it is typically energy intensive. To improve DSP energy efficiency for bio-based small molecules, integrating high-pressure membrane pre-concentration is a promising process option. However, this approach is typically constrained by a tradeoff between concentration factor (CF) and product recovery (PR), namely increasing the CF typically results in greater product loss, and vice versa. Here we developed a model that enables process design guidelines to: (i) identify scenarios in which the additional energy consumption and product loss from membrane pre-concentration are justified for use in DSP, and (ii) determine the optimal CF that minimizes process specific energy consumption. We compared the energy consumption of high-pressure membrane-integrated processes to evaporation-only processes and applied the model to an experimental case study for the separation and purification of butyric acid from Clostridium tyrobutyricum fermentation using an in situ product recovery (ISPR) process. The model estimated that integrating a tangential-flow reverse osmosis (RO) pre-concentration unit could reduce process energy consumption up to 45%. The use of advanced membrane pre-concentration technologies, such as negative rejection membranes and organic solvent reverse osmosis (OSRO), have the potential to further reduce the overall process specific energy consumption up to 96%, projected based on modeling. Overall, membrane pre-concentration, especially when strategically integrated prior to an evaporation step with optimized process conditions, holds significant potential for improving DSP energy efficiency, particularly in applications requiring substantial solvent removal for product recovery from dilute mixtures.
Fluorescence spectroscopy is a widely used sensor methodology that analyzes light emitted from a compound or element as it decays from an excited state. This technique is very sensitive and selective, which is ideal to characterize analytes at lower limits of detection. Key example targets of significant industry and research interest include rare earth elements (REEs) such as dysprosium (Dy) and europium (Eu). These are widely used in advanced technologies including semiconductors, electric vehicle motors, lasers, and permanent magnets. Identifying new sources and responsible reutilization of REEs is essential, and new approaches to extract and recycle REEs could be notably enhanced through the integration of on-line sensors. The sensors can support faster process design, informed scale-up, and cost-effective deployment. This study covers the initial exploration of applying fluorescence-based on-line monitoring to REEs within a precipitation process. This study demonstrates the successful scale-up of a fluorescence -based sensing approach, from stationary cuvettes and small-volume microfluidic devices to continuous flow systems operating at the bench scale (10-25mL). This work also provides initial insight into the challenges of signal’s effects and utility within a turbid environment. Using a modular design for monitoring flowing solutions in a flow tube, fluorescence can be characterized for a variety of analytical targets. In this study, detection performance parameters between the cuvette and flow tube system were compared. Additionally, the response of Dy during precipitation by sodium bicarbonate in the two measurement designs was explored. This letter represents a starting point to bridge the gap between traditional fluorescence sensor measurements in a cuvette to future developments that explore the ability to integrate fluorescence sensors into extraction and separation processes at industrially relevant scales.
To generate updated and transparent capital cost estimates for biomass fast pyrolysis equipment, refinery fluidized catalytic cracking design and sizing principles are examined and extended to pyrolysis of woody biomass. Capital costs for the sized equipment are estimated with process-industry software. A one-dimensional flow simulation with pyrolysis kinetics is leveraged to validate the fluidization conditions and thermal energy balance. After successful sizing and a system cost estimate of $\$$2.8 M (in 2016 US$\$$) at the biorefinery scale of 1000 metric tons per day (MTD), these methods were exercised for even smaller equipment at the distributed pyrolysis scale with modifications to the process design constraints, and not directly comparable with the 1000 MTD case, arriving at capital cost estimates of $\$$1.2 M for a 500 ton/day system and $\$$0.9 M for a 200 ton/day system. Here in this work, It is noted that this work only estimates purchased equipment costs at the ±50% accuracy level; there are significant other custom factors applicable to each installation based on location, maturity, scale, complexities during installation, engineering and licensing costs, etc. that need to be added on to these estimates to derive investment costs.
The Microgrid Design Toolkit (MDT) supports decision analysis for new ("greenfield") microgrid designs as well as microgrids with existing infrastructure. The current version of MDT includes two main capabilities. The first capability, the Microgrid Sizing Capability (MSC), is used to determine the size and composition of a new, grid connected microgrid in the early stages of the design process. MSC is focused on developing a microgrid that is economically viable when connected to the grid. The second capability is focused on designing a microgrid for operation in islanded mode. This second capability relies on two models: the Technology Management Optimization (TMO) model and Performance Reliability Model (PRM).
Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary heat transport system to ensure temperatures in the reactor systems, structures and components with significant safety margins during normal operation and design basis accident scenarios. This third semi-annual report summarized the progress made at Argonne on the two tasks during the first half of FY23. As a part of the RCCS design task, a design process for the water panel and the system configuration was performed to improve the thermal performance of the RCCS. The updated water panel design had achieved enhanced thermal performance with 0.96 MWth capability with major design updates made in structural interfaces with the RPV and initial configuration of the water tanks. The loop configuration of the RCCS has been proposed to have two independently working loops for system redundancy. A water panel material study was performed focusing on the use of carbon steel in water systems. Additional modeling strategies of primary system thermal fluids analyses were developed to meet modeling needs that are not well suited for the 1D-3D assembly level approach. The first of these is a reduced order assembly model, in which fuel centered unit cells are used to represent a fuel assembly. The 2D approach used in this model is much more computationally efficient, making this model useful for full core transient scenarios where fuel to coolant heat transfer is still the dominant flow path. The next model is the 3D core conduction model to be used to analyze decay heat removal in loss of primary system flow scenarios. Because these scenarios require a large domain to be modeled, a homogenized core model is being pursued to reduce the required computational costs. To accurately model decay heat scenarios it is necessary to couple a RCCS model to the 3D core conduction model. A simplified case is presented to demonstrate how the coupling methodology will be applied to the full core 3D conduction model.
Membrane gas separation processes have been developed for diverse gas separation applications that include nitrogen production from air and CO2 capture from point sources. Membrane process design requires the development of stable and robust mathematical models that can accurately quantify the performance of the membrane modules used in the process. The literature related to modeling membrane gas separation modules and model use in membrane gas separation process simulators is reviewed in this paper. A membrane-module-modeling checklist is proposed to guide modeling efforts for the research and development of new gas separation membranes.