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At least 289 records · Page 16

Astronaut Office Scheduling System Software

AOSS is a highly efficient scheduling application that uses various tools to schedule astronauts weekly appointment information. This program represents an integration of many technologies into a single application to facilitate schedule sharing and management. It is a Windows-based application developed in Visual Basic. Because the NASA standard office automation load environment is Microsoft-based, Visual Basic provides AO SS developers with the ability to interact with Windows collaboration components by accessing objects models from applications like Outlook and Excel. This also gives developers the ability to create newly customizable components that perform specialized tasks pertaining to scheduling reporting inside the application. With this capability, AOSS can perform various asynchronous tasks, such as gathering/ sending/ managing astronauts schedule information directly to their Outlook calendars at any time.

Brown, Estevancio↗

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Enhanced deep neural networks with transfer learning for distribution LMP considering load and PV uncertainties

As the flexibility of generation and demand increases in distribution systems, the residential loads are emerging as a promising means to participate in demand response and the transactive energy market. Market pricing is an instrumental mechanism for the distribution system operator to exploit the full potential of the flexible resources. The distribution locational marginal price (DLMP) can be used to guide the residential load consumption. This type of market signal helps the distribution system operator to optimize the scheduling of all resources while satisfying related network constraints through a day-ahead market. However, solving the optimization problem for large-scale systems can be computationally expensive. To address the scalability and practicability limitations of the DLMP framework, a learning-based approach is proposed in this paper to complement the day-ahead distribution market framework. Here, the proposed approach combines long short-term memory and transfer learning to develop deep neural network that can capture the spatial–temporal correlation of the input data. The model can determine the optimal DLMP for each node in a distribution system without the system parameters required to formulate the optimization problem. Testing results on IEEE 33-bus and 123-bus systems show that the proposed approach can generate a comparable DLMP against the optimization solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Photovoltaic system criteria documents. Volume 1: Guidelines for evaluating the management and operations planning of photovoltaic applications

Guidelines are provided to the Field Centers for organization, scheduling, project and cost control, and performance in the areas of project management and operations planning for Photovoltaics Test and Applications. These guidelines may be used in organizing a T and A Project Team for system design/test, site construction and operation, and as the basis for evaluating T and A proposals. The attributes are described for project management and operations planning to be used by the Field Centers. Specifically, all project management and operational issues affecting costs, schedules and performance of photovoltaic systems are addressed. Photovoltaic tests and applications include residential, intermediate load center, central station, and stand-alone systems. The sub-categories of system maturity considered are: Initial System Evaluation Experiments (ISEE); System Readiness Experiments (SRE); and Commercial Readiness Demonstration Projects (CRDP).

Koenig, John C.↗

Surface Systems Capability Gaps for Enabling NASA’s Sustainable Lunar Operations

This paper discusses the NASA Ground, Test, and Surface Systems Taxonomy (TX-13) related capability gaps, including details of architecture, technology, engineering, and policy gaps for enabling sustainable lunar surface operations and subsequent Mars missions. Architecture gaps include standardized architectures and interfaces, multi-element systems engineering and integration, design for supportability, and nuclear payload processing and launch approach. Technology gaps, primarily focused on uncrewed surface operations, include automated/autonomous cryogenic loading, transfer, servicing, and storage of commodities; health determination and fault management; automated/autonomous planning and scheduling; automated/autonomous inspection, maintenance and repair; logistics management and reliability; launch and landing site preparation; commodity management; and advanced umbilicals and dust tolerant interfaces. Engineering gaps include high-purity propellant production for ground and surface applications and large-scale xenon servicing capabilities. The policy gap includes nuclear propulsion acceptance testing and qualification approach. Strategically identifying human/automation roles and tasks and infusing automation and autonomy practices early in a system’s lifecycle is essential for achieving the mission objectives for a sustainable human lunar presence, improving performance and mission effectiveness, reducing operations costs and reliance on humans to perform tasks, and accommodating ground communication delays.

Surface Systems↗

DSN Resource Scheduling

TIGRAS is client-side software, which provides tracking-station equipment planning, allocation, and scheduling services to the DSMS (Deep Space Mission System). TIGRAS provides functions for schedulers to coordinate the DSN (Deep Space Network) antenna usage time and to resolve the resource usage conflicts among tracking passes, antenna calibrations, maintenance, and system testing activities. TIGRAS provides a fully integrated multi-pane graphical user interface for all scheduling operations. This is a great improvement over the legacy VAX VMS command line user interface. TIGRAS has the capability to handle all DSN resource scheduling aspects from long-range to real time. TIGRAS assists NASA mission operations for DSN tracking of station equipment resource request processes from long-range load forecasts (ten years or longer), to midrange, short-range, and real-time (less than one week) emergency tracking plan changes. TIGRAS can be operated by NASA mission operations worldwide to make schedule requests for the DSN station equipment.

Wang, Yeou-Fang↗

A comparison of hand grasp breakaway strengths and bare-handed grip strengths of the astronauts, SML 3 test subjects, and the subjects from the general population

Astronauts have the task of retrieving and deploying satellites and handling massive objects in a around the payload bay. Concerns were raised that manual handling of such massive objects might induce loads to the shuttle suits exceeding the design-certified loads. The Crew and Thermal Division of NASA JSC simulated the satellite handling tasks (Satellite Manload Tests 1 and 3) and determined the maximum possible load that a suited member could impart onto the suit. In addition, the tests revealed that the load to the suit by an astronaut could be calculated from the astronaut's maximum hand grasp breakaway strength. Thus, this study was conducted to document that hand grasp breakaway strengths of the astronauts who were scheduled to perform EVA during the upcoming missions. In addition, this study verified whether the SML 3 test results were sufficient for documenting the maximum possible load. An attempt was made to predict grasp strength from grip strength and hand anthropometry. Based on the results from this study, the SML 3 test results were deemed sufficient to document the maximum possible load on the suit. Finally, prediction of grasp strength from grip strength was not as accurate as expected. Hence, it was recommended that grasp strength be collected from the astronauts in order to obtain accurate load estimation.

Rajulu, Sudhakar L.↗

The Summer of Hydrogen

Ground crew veterans at Kennedy Space Center still talk about what they call "the summer of hydrogen"-the long, frustrating months in 1990 when the shuttle fleet was grounded by an elusive hydrogen leak that foiled our efforts to fill the orbiter's external fuel tank. Columbia (STS-35) was on Launch Pad A for a scheduled May 30 launch when we discovered the hydrogen leak during - tanking. The external fuel tank is loaded through the orbiter. Liquid hydrogen flows through a 17-inch umbilical between the orbiter and the tank. During fueling, we purge the aft fuselage with gaseous nitrogen to reduce the risk of fire, and we have a leak-detection system in the mobile launch platform, which samples (via tygon tubing) the atmosphere in and around the vehicle, drawing it down to a mass spectrometer that analyzes its composition. When we progressed to the stage of tanking where liquid hydrogen flows through the vehicle, the concentration of hydrogen approached four percent-the limit above which it would be dangerously flammable. We had a leak. We did everything we could think of to find it, and the contractor who supplied the flight hardware was there every day, working alongside us. We did tanking tests, which involved instrumenting the suspected leak sources, and cryo-loaded the external tank to try to isolate precisely where the leak originated. We switched out umbilicals; we replaced the seals between the umbilical and the orbiter. We inspected the seals microscopically and found no flaws. We replaced the recirculation pumps, and we found and replaced a damaged teflon seal in a main propulsion system detent cover, which holds the prevalve-the main valve supplying hydrogen to Space Shuttle Main Engine 3 -in the open position. The seal passed leak tests at ambient temperature but leaked when cryogenic temperatures were applied. We added new leak sensors-up to twenty at a time and tried to be methodical in our placements to narrow down the possible sources of the problem. We even switched orbiters, sending Columbia back to the Vehicle Assembly Building and bringing out Atlantis, scheduled to fly as STS-38. Two shuttles on their mobile launchers passing in the night was a majestic sight, but not one you want to see if you're trying to get an orbiter launched. None of this told us where the leak was, or if we were dealing with more than one leak source.

Weber, Philip↗

Design considerations for a Digital Twin built to improve nitrification performance at a water resource recovery facility

A Digital Twin built around Activated Sludge Model No. 1 was deployed at a full-scale water resource recovery facility. Its design included a waste rate recommender system based on automatic scenario analyses, where influent loads and waste rates are varied to determine their impact on nitrification. At the same frequency as these scenario analyses, scheduled auto-calibrations allow for nitrifier maximum specific growth rate (μmax-NITO) soft sensing, the only kinetic parameter shown to require adjustment if the objective is aeration tank effluent ammonia forecasting accuracy. By integrating temperature forecasting over the next three sludge ages, this Digital Twin approach creates opportunities for advancing waste rate decisions in anticipation of seasonal temperature changes, optimizing ammonia control authority under varying influent loads, and furnishing valuable insights for future capital projects requiring nitrifier kinetic understanding and modelling.

54 ENVIRONMENTAL SCIENCES↗

Development and evaluation of a Fault-Tolerant Multiprocessor (FTMP) computer. Volume 2: FTMP software

The software developed for the Fault-Tolerant Multiprocessor (FTMP) is described. The FTMP executive is a timer-interrupt driven dispatcher that schedules iterative tasks which run at 3.125, 12.5, and 25 Hz. Major tasks which run under the executive include system configuration control, flight control, and display. The flight control task includes autopilot and autoland functions for a jet transport aircraft. System Displays include status displays of all hardware elements (processors, memories, I/O ports, buses), failure log displays showing transient and hard faults, and an autopilot display. All software is in a higher order language (AED, an ALGOL derivative). The executive is a fully distributed general purpose executive which automatically balances the load among available processor triads. Provisions for graceful performance degradation under processing overload are an integral part of the scheduling algorithms.

Lala, J. H.↗

Stochastic simulation of occupant-driven energy use in a bottom-up residential building stock model

The residential buildings sector is one of the largest electricity consumers worldwide and contributes disproportionally to peak electricity demand in many regions. Strongly driven by occupant activities, household energy consumption is stochastic and heterogeneous in nature. However, most residential energy models applied by industry use homogeneous, deterministic activity schedules, which work well for predictions of annual energy consumption, but can result in unrealistic hourly or sub-hourly electric load profiles, with exaggerated or muted peaks. The increasing proportion of variable renewable energy generators means that representing the heterogeneity and stochasticity of occupant behavior is now crucial for reliable planning at both bulk-power and distribution-system scales. This work presents a novel and open-source occupancy simulation approach that can simulate a diverse set of individual occupant and household event schedules for all major electricity, fuel, and hot water end uses. To accomplish this, we evaluated three alternative occupant activity simulation approaches before selecting a hybrid combining time-inhomogeneous Markov chains and probability-sampling of event durations and magnitudes. Further, we integrated the stochastic occupancy simulation with an open-source bottom-up physics-simulation building stock model and published a set of 550,000 diverse household end-use activity schedules representing a national housing stock. The simulator was verified against time-use survey data, and simulation results were validated against measured end-use electricity data for accuracy and reliability. While we use data for the United States, our application demonstrates how similar approaches could be applied using the time-use survey data collected in many countries around the world.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Asynchronous distributed-memory task-parallel algorithm for compressible flows on unstructured 3D Eulerian grids

Here, we discuss the implementation of a finite element method, used to numerically solve the Euler equations of compressible flows, using an asynchronous runtime system (RTS). The algorithm is implemented for distributed-memory machines, using stationary unstructured 3D meshes, combining data-, and task-parallelism on top of the Charm++ RTS. Charm++’s execution model is asynchronous by default, allowing arbitrary overlap of computation and communication. Task-parallelism allows scheduling parts of an algorithm independently of, or dependent on, each other. Built-in automatic load balancing enables continuous redistribution of computational load by migration of work units based on real-time CPU load measurement. The RTS also features automatic checkpointing, fault tolerance, resilience against hardware failure, and supports power-, and energy-aware computation. We demonstrate scalability up to 25 x 10 9 cells at $\mathscr{O}$10 4 compute cores and the benefits of automatic load balancing for irregular workloads. The full source code with documentation is available at https://quinoacomputing.org.

42 ENGINEERING↗

Rocketdyne LOX bearing tester program

The cause, or causes, for the Space Shuttle Main Engine ball wear were unknown, however, several mechanisms were suspected. Two testers were designed and built for operation in liquid oxygen to empirically gain insight into the problems and iterate solutions in a timely and cost efficient manner independent of engine testing. Schedules and test plans were developed that defined a test matrix consisting of parametric variations of loading, cooling or vapor margin, cage lubrication, material, and geometry studies. Initial test results indicated that the low pressure pump thrust bearing surface distress is a function of high axial load. Initial high pressure turbopump bearing tests produced the wear phenomenon observed in the turbopump and identified an inadequate vapor margin problem and a coolant flowrate sensitivity issue. These tests provided calibration data of analytical model predictions to give high confidence in the positive impact of future turbopump design modification for flight. Various modifications will be evaluated in these testers, since similar turbopump conditions can be produced and the benefit of the modification will be quantified in measured wear life comparisons.

Keba, J. E.↗

Thermostructural Qualification of PICA-D for NASA Planetary Science Missions

Phenolic Impregnated Carbon Ablator (PICA) has been used as the heatshield TPS material for many NASA planetary science missions. Due to a supply issue with the heritage Rayon fibers used in PICA fabrication, NASA started a project in 2017 to develop a sustainable replacement for PICA using a domestic fiber source, named PICA-D. This material has been selected as the heatshield TPS material for two upcoming NASA planetary science missions, Dragonfly mission to Titan and Mars Sample Retrieval Lander (SRL). While most PICA-D thermal and mechanical properties are very similar to PICA, early test data suggest that PICA-D is stiffer in tension in the in-plane (IP) direction, with higher strength but lower strain-to-failure. Preliminary thermostructural analysis using Finite Element Methods (FEM) tools predict IP compressive failure in the near-surface layers of PICA-D, for both Dragonfly and SRL flight environments. This talk provides an overview of the thermostructural qualification plans for PICA-D. A two-pronged approach is being pursued to demonstrate that the material and heatshield design has adequate capability for both SRL and Dragonfly design environments. The first part is to improve the accuracy of analytical predictions through a comprehensive characterization of PICA-D mechanical properties. The second, and more critical, part of the qualification approach is a subsystem-level test of PICA-D to demonstrate material capability under flight-relevant combined mechanical and thermal loads. The team is currently preparing for two test series in Sandia’s Solar Tower facility, scheduled in September 2023 and focusing on PICA-D acreage, followed by additional tests in the Solar Tower and LHMEL facilities focusing on design features and repair methods.

TPS↗

Stochastic Microgrid Scheduling With Chance‐Constrained Resilience Consideration

Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.

chance constrained optimization↗

Advanced Sensor Platform to Evaluate Manloads For Exploration Suit Architectures

Space suit manloads are defined as the outer bounds of force that the human occupant of a suit is able to exert onto the suit during motion. They are defined on a suit-component basis as a unit of maximum force that the suit component in question must withstand without failure. Existing legacy manloads requirements are specific to the suit architecture of the EMU and were developed in an iterative fashion; however, future exploration needs dictate a new suit architecture with bearings, load paths, and entry capability not previously used in any flight suit. No capability currently exists to easily evaluate manloads imparted by a suited occupant, which would be required to develop requirements for a flight-rated design. However, sensor technology has now progressed to the point where an easily-deployable, repeatable and flexible manloads measuring technique could be developed leveraging recent advances in sensor technology. INNOVATION: This development positively impacts schedule, cost and safety risk associated with new suit exploration architectures. For a final flight design, a comprehensive and accurate man loads requirements set must be communicated to the contractor; failing that, a suit design which does not meet necessary manloads limits is prone to failure during testing or worse, during an EVA, which could cause catastrophic failure of the pressure garment posing risk to the crew. This work facilitates a viable means of developing manloads requirements using a range of human sizes & strengths. OUTCOME / RESULTS: Performed sensor market research. Highlighted three viable options (primary, secondary, and flexible packaging option). Designed/fabricated custom bracket to evaluate primary option on a single suit axial. Manned suited manload testing completed and general approach verified.

McFarland, Shane↗

On the role of Battery Energy Storage Systems in the day-ahead Contingency-Constrained Unit Commitment problem under renewable penetration

The integration of variable Renewable Energy Sources (vRES) to alleviate greenhouse gas emissions has introduced significant challenges for power systems operations. These challenges include high levels of uncertainty due to the intermittence associated with vRES and therefore impose the need to devise a reliable and cost-effective day-ahead unit commitment and power and reserves scheduling for real-time operations. Also, this increasing penetration of vRES requires higher ramping capabilities from units originally designed for other purposes (e.g., base-load generation), which might be exacerbated during contingency states. Hence, in this work, we propose a methodology to address the day-ahead Contingency-Constrained Unit Commitment (CCUC) problem that leverages the participation of Battery Energy Storage Systems (BESSs) to address load-following and post-contingency management, therefore alleviating the ramping burden on conventional thermal generators. To do so, we formulate a three-level optimization problem that represents the decision-making process of obtaining the least-cost commitment, generation and reserves scheduling, while restricting the Conditional Value-at-Risk (CVaR) of the system imbalance at real-time operations to user-defined tolerance levels. In addition, we devise a computationally efficient solution approach for the proposed problem based on the Column-and Constraint Generation (CCG) algorithmic framework. Two numerical experiments are conducted to empirically illustrate the benefits of the proposed methodology. Key results indicate a reduction in real-time ramping needs and a better usage of the system resources, with a reduction in the overall system commitment levels and reserve scheduling costs when compared to a benchmark case in which storage is not available.

Moreira, Alexandre↗