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This paper describes the Automated Scheduling and Planning Environment (ASPEN). ASPEN encodes complex spacecraft knowledge of operability constraints, flight rules, spacecraft hardware, science experiments and operations procedures to allow for automated generation of low level spacecraft sequences.
Spatial acquisition and precision beam pointing functions are critical to spaceborne laser communication systems. A recent system study indicated that a single high bandwidth CCD detector can be used to perform both spatial acquisition and tracking functions. Compared to previous lasercom hardware design, the arrray tracking cocept offers reduced system complexity by reducing the number of optical elements in the design.
This work describes the design and development effort to adapt rapid-development space hardware by creating a ground system using solutions of low complexity, mass, & cost. The Lunar Atmosphere and Dust Environment Explorer (LADEE) spacecraft is based on the modular common spacecraft bus architecture developed at NASA Ames Research Center. The challenge was building upon the existing modular common bus design and development work and improving the LADEE spacecraft design by adding an Equipotential Voltage Reference (EVeR) system, commonly referred to as a ground system. This would aid LADEE in meeting Electromagnetic Environmental Effects (E3) requirements, thereby making the spacecraft more compatible with itself and its space environment. The methods used to adapt existing hardware are presented, including provisions which may be used on future spacecraft.
The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms have, however, failed to provide strong scaling for MD, as scale-out central processing unit (CPU) and graphics processing unit (GPU) platforms that provide substantial increases to spatial scale do not lead to proportional increases in temporal scale. Important scientific problems therefore remained inaccessible to direct simulation, prompting the development of increasingly sophisticated algorithms that present significant complexity, accuracy, and efficiency challenges. While bespoke MD-only hardware solutions have provided a path to longer timescales for specific physical systems, their impact on the broader community has been mitigated by their limited adaptability to new methods and potentials. In this work, we show that a novel computing architecture, the Cerebras wafer scale engine, completely alters the scaling path by delivering unprecedentedly high simulation rates up to 1.144 M steps/s for 200 000 atoms whose interactions are described by an embedded atom method potential. This enables direct simulations of the evolution of materials using general-purpose programmable hardware over millisecond timescales, dramatically increasing the space of direct MD simulations that can be carried out. In this paper, we provide an overview of advances in MD over the last 60 years and present our recent result in the context of historical MD performance trends.
Identification of innovative solutions to unique materials problems is an every-day quest for members of the aerospace community. Finding a technique that will minimize costs, maximize throughput, and generate quality results is always the target. United Space Alliance Materials Engineers recently conducted such a search in their drive to return the Space Shuttle fleet to operational status. The removal of high performance thermal coatings from solid rocket motors represents a formidable task during post flight disassembly on reusable expended hardware. The removal of these coatings from unfired motors increases the complexity and safety requirements while reducing the available facilities and approved processes. A temporary solution to this problem was identified, tested and approved during the Solid Rocket Booster (SRB) return to flight activities. Utilization of ultra high-pressure liquid nitrogen (LN2) to strip the protective coating from assembled space shuttle hardware marked the first such use of the technology in the aerospace industry. This process provides a configurable stream of liquid nitrogen (LN2) at pressures of up to 55,000 psig. The performance of a one-time certification for the removal of thermal ablatives from SRB hardware involved extensive testing to ensure adequate material removal without causing undesirable damage to the residual materials or aluminum substrates. Testing to establish appropriate process parameters such as flow, temperature and pressures of the liquid nitrogen stream provided an initial benchmark for process testing. Equipped with these initial parameters engineers were then able to establish more detailed test criteria that set the process limits. Quantifying the potential for aluminum hardware damage represented the greatest hurdle for satisfying engineers as to the safety of this process. Extensive testing for aluminum erosion, surface profiling, and substrate weight loss was performed. This successful project clearly demonstrated that the liquid nitrogen jet possesses unique strengths that align remarkably well with the unusual challenges that space hardware and missile manufacturers face on a regular basis. Performance of this task within the confines of a critical manufacturing facility marks a milestone in advanced processing.
The satellite systems Fault Management (FM) is focused on safety, the preservation of assets, and maintaining the desired functionality of the system. How FM is implemented varies among missions. Common to most is system complexity due to a need to establish a multi-dimensional structure across hardware, software and operations. This structure is necessary to identify and respond to system faults, mitigate technical risks and ensure operational continuity. These architecture, implementation and software assurance efforts increase with mission complexity. Because FM is a systems engineering discipline with a distributed implementation, providing efficient and effective verification and validation (VV) is challenging. A breakout session at the 2012 NASA Independent Verification Validation (IVV) Annual Workshop titled VV of Fault Management: Challenges and Successes exposed these issues in terms of VV for a representative set of architectures. NASA's IVV is funded by NASA's Software Assurance Research Program (SARP) in partnership with NASA's Jet Propulsion Laboratory (JPL) to extend the work performed at the Workshop session. NASA IVV will extract FM architectures across the IVV portfolio and evaluate the data set for robustness, assess visibility for validation and test, and define software assurance methods that could be applied to the various architectures and designs. This work focuses efforts on FM architectures from critical and complex projects within NASA. The identification of particular FM architectures, visibility, and associated VVIVV techniques provides a data set that can enable higher assurance that a satellite system will adequately detect and respond to adverse conditions. Ultimately, results from this activity will be incorporated into the NASA Fault Management Handbook providing dissemination across NASA, other agencies and the satellite community. This paper discusses the approach taken to perform the evaluations and preliminary findings from the research including identification of FM architectures, visibility observations, and methods utilized for VVIVV.
Trilinos is a community-developed, open-source software framework that facilitates building large-scale, complex, multiscale, multiphysics simulation code bases for scientific and engineering problems. Since the Trilinos framework has undergone substantial changes to support new applications and new hardware architectures, this document is an update to “An Overview of the Trilinos project” by Heroux et al. (ACM Transactions on Mathematical Software, 31(3):397–423, 2005). It describes the design of Trilinos, introduces its new organization in product areas, and highlights established and new features available in Trilinos. Particular focus is put on the modernized software stack based on the Kokkos ecosystem to deliver performance portability across heterogeneous hardware architectures. This article also outlines the organization of the Trilinos community and the contribution model to help onboard interested users and contributors.
Fault Management (FM) is focused on safety, the preservation of assets, and maintaining the desired functionality of the system. How FM is implemented varies among missions. Common to most missions is system complexity due to a need to establish a multi-dimensional structure across hardware, software and spacecraft operations. FM is necessary to identify and respond to system faults, mitigate technical risks and ensure operational continuity. Generally, FM architecture, implementation, and software assurance efforts increase with mission complexity. Because FM is a systems engineering discipline with a distributed implementation, providing efficient and effective verification and validation (V&V) is challenging. A breakout session at the 2012 NASA Independent Verification & Validation (IV&V) Annual Workshop titled "V&V of Fault Management: Challenges and Successes" exposed this issue in terms of V&V for a representative set of architectures. NASA's Software Assurance Research Program (SARP) has provided funds to NASA IV&V to extend the work performed at the Workshop session in partnership with NASA's Jet Propulsion Laboratory (JPL). NASA IV&V will extract FM architectures across the IV&V portfolio and evaluate the data set, assess visibility for validation and test, and define software assurance methods that could be applied to the various architectures and designs. This SARP initiative focuses efforts on FM architectures from critical and complex projects within NASA. The identification of particular FM architectures and associated V&V/IV&V techniques provides a data set that can enable improved assurance that a system will adequately detect and respond to adverse conditions. Ultimately, results from this activity will be incorporated into the NASA Fault Management Handbook providing dissemination across NASA, other agencies and the space community. This paper discusses the approach taken to perform the evaluations and preliminary findings from the research.
The proposed paper will focus on the Project Management and Systems Engineering approach utilized to develop a set of both integrated and cohesive requirements for the Exploration Launch Office, within the Constellation Program. A summary of the programmatic drivers which influenced the approach along with details of the resulting implementation will be discussed as well as metrics evaluating the efficiency and accuracy of the various requirements development activities. Requirements development activities will focus on the procedures utilized to ensure that technical content was valid and mature in preparation for the Crew Launch Vehicle and Constellation System s Requirements Reviews. This discussion will begin at initial requirements development during the Exploration Systems Architecture Study and progress through formal development of the program structure. Specific emphasis will be given to development and validation of the requirements. This discussion will focus on approaches to garner the appropriate requirement owners (or customers), project infrastructure utilized to emphasize proper integration, and finally the procedure to technically mature, verify and validate the requirements. Examples of requirements being implemented on the Launch Vehicle (systems, interfaces, test & verification) will be utilized to demonstrate the various processes and also provide a top level understanding of the launch vehicle(s) performance goals. Details may also be provided on the approaches for verification, which range from typical aerospace hardware development (qualification/acceptance) through flight certification (flight test, etc.). The primary intent of this paper is to provide a demonstrated procedure for the development of a mature, effective, integrated set of requirements on a complex system, which also has the added intricacies of both heritage and new hardware development integration. Ancillary focus of the paper will include discussion of Test and Verification approaches along with top level systems/elements performance capabilities.
This paper describes the approach used by the Space Communication and Navigation (SCaN) Testbed team to qualify three Software Defined Radios (SDR) for operation in space and the characterization of the platform to enable upgrades on-orbit. The three SDRs represent a significant portion of the new technologies being studied on board the SCAN Testbed, which is operating on an external truss on the International Space Station (ISS). The SCaN Testbed provides experimenters an opportunity to develop and demonstrate experimental waveforms and applications for communication, networking, and navigation concepts and advance the understanding of developing and operating SDRs in space. Qualifying a Software Defined Radio for the space environment requires additional consideration versus a hardware radio. Tests that incorporate characterization of the platform to provide information necessary for future waveforms, which might exercise extended capabilities of the hardware, are needed. The development life cycle for the radio follows the software development life cycle, where changes can be incorporated at various stages of development and test. It also enables flexibility to be added with minor additional effort. Although this provides tremendous advantages, managing the complexity inherent in a software implementation requires a testing beyond the traditional hardware radio test plan. Due to schedule and resource limitations and parallel development activities, the subsystem testing of the SDRs at the vendor sites was primarily limited to typical fixed transceiver type of testing. NASA s Glenn Research Center (GRC) was responsible for the integration and testing of the SDRs into the SCaN Testbed system and conducting the investigation of the SDR to advance the technology to be accepted by missions. This paper will describe the unique tests that were conducted at both the subsystem and system level, including environmental testing, and present results. For example, test waveforms were developed to measure the gain of the transmit system across the tunable frequency band. These were used during thermal vacuum testing to enable characterization of the integrated system in the wide operational temperature range of space. Receive power indicators were used for Electromagnetic Interference tests (EMI) to understand the platform s susceptibility to external interferers independent of the waveform. Additional approaches and lessons learned during the SCaN Testbed subsystem and system level testing will be discussed that may help future SDR integrators
This paper describes the approach used by the Space Communication and Navigation (SCaN) Testbed team to qualify three Software Defined Radios (SDR) for operation in space and the characterization of the platform to enable upgrades on-orbit. The three SDRs represent a significant portion of the new technologies being studied on board the SCAN Testbed, which is operating on an external truss on the International Space Station (ISS). The SCaN Testbed provides experimenters an opportunity to develop and demonstrate experimental waveforms and applications for communication, networking, and navigation concepts and advance the understanding of developing and operating SDRs in space. Qualifying a Software Defined Radio for the space environment requires additional consideration versus a hardware radio. Tests that incorporate characterization of the platform to provide information necessary for future waveforms, which might exercise extended capabilities of the hardware, are needed. The development life cycle for the radio follows the software development life cycle, where changes can be incorporated at various stages of development and test. It also enables flexibility to be added with minor additional effort. Although this provides tremendous advantages, managing the complexity inherent in a software implementation requires a testing beyond the traditional hardware radio test plan. Due to schedule and resource limitations and parallel development activities, the subsystem testing of the SDRs at the vendor sites was primarily limited to typical fixed transceiver type of testing. NASA's Glenn Research Center (GRC) was responsible for the integration and testing of the SDRs into the SCaN Testbed system and conducting the investigation of the SDR to advance the technology to be accepted by missions. This paper will describe the unique tests that were conducted at both the subsystem and system level, including environmental testing, and present results. For example, test waveforms were developed to measure the gain of the transmit system across the tunable frequency band. These were used during thermal vacuum testing to enable characterization of the integrated system in the wide operational temperature range of space. Receive power indicators were used for Electromagnetic Interference tests (EMI) to understand the platform's susceptibility to external interferers independent of the waveform. Additional approaches and lessons learned during the SCaN Testbed subsystem and system level testing will be discussed that may help future SDR integrators.
Automated ventilator controllers have the potential to simplify oxygen and carbon dioxide management for trauma. In the pre-hospital or military medicine environment, trauma care can be required for prolonged periods by personnel with limited ventilator management training. As such, there is a need for closed-loop control systems that can adapt ventilator management to a complex, ever-changing medical environment. Here, we present a novel hardware-in-loop test platform for the independent troubleshooting and evaluation of oxygen and carbon dioxide automated ventilator management capabilities. The oxygen management system provides an analogue blood oxygen signal that is responsive to the fraction of inspired oxygen and the peak inspiratory pressure ventilator settings. A tested oxygenation controller successfully reached the target oxygen saturation within 5 min. The carbon dioxide removal system integrates with commercial ventilator technology and mimics carbon dioxide generation, lung compliance, and airway resistance while providing an end-tidal carbon dioxide level that is responsive to changes in the tidal volume and respiratory rate settings. A test mechanical ventilator controller was able to regulate EtCO2 regardless of the starting value within 10 min. This highlights the system’s functionality and provides proof-of-concept demonstrations for how the hardware-in-loop test platforms can be used for evaluating closed-loop controller technologies.
The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.
The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.
Volt-VAR control (VVC) is crucial in active distribution networks for optimizing voltage profiles and minimizing network losses. While traditional deep reinforcement learning (DRL) algorithms exhibit promise for VVC, they often require extensive computational resources to handle such a high-dimensional problem. As a potential solution, quantum reinforcement learning (QRL) algorithms integrate the computational capabilities of quantum computing into the DRL framework. However, existing QRL algorithms struggle with complex VVC problems due to the limitations of current quantum hardware. To bridge this gap, this paper proposes an innovative QRL algorithm featuring an end-to-end architecture that integrates a classical autoencoder, variational quantum circuits (VQCs), and classical post-processing layers. This design efficiently compresses high-dimensional grid states, enabling VQCs to leverage quantum advantages while producing multiple control device outputs tailored for VVC tasks. Numerical studies on three representative distribution systems verify the effectiveness and scalability of the proposed QRL algorithm, and demonstrate its enhanced performance over classical approaches with only approximately 1% of the parameters. Additionally, the robustness of our developed algorithm is validated through noisy quantum environments.
he PIP-II Accelerator is an 800 MeV superconducting Linac in the injection chain of the Fermilab accelerator complex. The LLRF systems are a based on two different hardware platforms controlling a variety of cavity types and resonance control systems including temperature, pneumatic and piezzo tuners. The various calibrations required prior to beam operation include, signal power, gradient, amplifier characterization, cavity Q measurement and detune constants. Measurements such as piezzo capacitance, cavity piezo transfer function help in determining tuner health and in devising microphonics control strategies. These measurement and calibration methods of the PIP-II LLRF system are discussed here.
The paper outlines the approach used in developing DMS (Data Management Subsystem) alternatives for the LST (Large Space Telescope) and in selecting the concept considered to be the most cost effective means of implementing the LST DMS requirements. Two candidate DMS concepts are discussed: a functionally integrated and a functionally separated one. For the single vehicle LST program, separation of the DMS functions best provides high reliability, operations flexibility, minimal interface complexity, and the least complex software development and verification task. The use of available hardware and NASA standard components is stressed.
As the hardware trends for artificial intelligence (AI) involve more and more complexity, the process of optimizing the computer system design for a particular problem will also increase in complexity. Space applications of knowledge based systems (KBS) will often require an ability to perform both numerically intensive vector computations and real time symbolic computations. Although parallel machines can theoretically achieve the speeds necessary for most of these problems, if the application itself is not highly parallel, the machine's power cannot be utilized. A scheme is presented which will provide the computer systems engineer with a tool for analyzing machines with various configurations of array, symbolic, scaler, and multiprocessors. High speed networks and interconnections make customized, distributed, intelligent systems feasible for the application of AI in space. The method presented can be used to optimize such AI system configurations and to make comparisons between existing computer systems. It is an open question whether or not, for a given mission requirement, a suitable computer system design can be constructed for any amount of money.