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At least 1,243 records · Page 69

A Modular Framework for Modeling Hardware Elements in Distributed Engine Control Systems

Progress toward the implementation of distributed engine control in an aerospace application may be accelerated through the development of a hardware-in-the-loop (HIL) system for testing new control architectures and hardware outside of a physical test cell environment. One component required in an HIL simulation system is a high-fidelity model of the control platform: sensors, actuators, and the control law. The control system developed for the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) provides a verifiable baseline for development of a model for simulating a distributed control architecture. This distributed controller model will contain enhanced hardware models, capturing the dynamics of the transducer and the effects of data processing, and a model of the controller network. A multilevel framework is presented that establishes three sets of interfaces in the control platform: communication with the engine (through sensors and actuators), communication between hardware and controller (over a network), and the physical connections within individual pieces of hardware. This introduces modularity at each level of the model, encouraging collaboration in the development and testing of various control schemes or hardware designs. At the hardware level, this modularity is leveraged through the creation of a Simulink(R) library containing blocks for constructing smart transducer models complying with the IEEE 1451 specification. These hardware models were incorporated in a distributed version of the baseline C-MAPSS40k controller and simulations were run to compare the performance of the two models. The overall tracking ability differed only due to quantization effects in the feedback measurements in the distributed controller. Additionally, it was also found that the added complexity of the smart transducer models did not prevent real-time operation of the distributed controller model, a requirement of an HIL system.

numerical simulation↗

A Modular Framework for Modeling Hardware Elements in Distributed Engine Control Systems

Progress toward the implementation of distributed engine control in an aerospace application may be accelerated through the development of a hardware-in-the-loop (HIL) system for testing new control architectures and hardware outside of a physical test cell environment. One component required in an HIL simulation system is a high-fidelity model of the control platform: sensors, actuators, and the control law. The control system developed for the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) provides a verifiable baseline for development of a model for simulating a distributed control architecture. This distributed controller model will contain enhanced hardware models, capturing the dynamics of the transducer and the effects of data processing, and a model of the controller network. A multilevel framework is presented that establishes three sets of interfaces in the control platform: communication with the engine (through sensors and actuators), communication between hardware and controller (over a network), and the physical connections within individual pieces of hardware. This introduces modularity at each level of the model, encouraging collaboration in the development and testing of various control schemes or hardware designs. At the hardware level, this modularity is leveraged through the creation of a SimulinkR library containing blocks for constructing smart transducer models complying with the IEEE 1451 specification. These hardware models were incorporated in a distributed version of the baseline C-MAPSS40k controller and simulations were run to compare the performance of the two models. The overall tracking ability differed only due to quantization effects in the feedback measurements in the distributed controller. Additionally, it was also found that the added complexity of the smart transducer models did not prevent real-time operation of the distributed controller model, a requirement of an HIL system.

propulsion simulation↗

Model Development and Analysis of a High-Fidelity Neutron Transport Sensor: The Quadrupole Detector Concept for Measurement of the Neutron Flux Gradient

Accurate reconstruction of the neutron flux distribution within a reactor core is essential for safe and efficient reactor operation. Traditional power shape synthesis in Light Water Reactors relies on hundreds of in-core detectors. However, this approach becomes impractical for Advanced Reactors and Microreactors due to limited space and harsh environments. To address this challenge, we propose a data-driven methodology that combines high-fidelity modeling with real-time ex-core sensor measurements, enabling the reconstruction of core power distribution while minimizing the reliance on intrusive in-core instrumentation. This project began in FY24 and achieved two initial milestones: (1) the definition of a three-year development plan for a Digital Twin framework and (2) the development of high-fidelity neutronics models of the Purdue University Reactor One (PUR-1) using both MCNP6 and OpenMC. The PUR-1 reactor, a zero-power facility, was selected due to its suitability for neutronics-focused modeling and the availability of experimental data for validation. Both models were benchmarked using neutron flux measurements obtained from irradiated gold foils, which were strategically placed within the core during a dedicated campaign in July 2024. This report marks the continuation and completion of those foundational tasks. The OpenMC model has been refined (improved geometric accuracy, expanded cross-section libraries, and refined sampling) and validated using additional experimental data. An updated sensor design—based on quadrupole configuration—was designed to measure both ex-core flux and its spatial gradient. These measurements will serve as inputs to a neural network-based reconstruction algorithm. Finally, the methodology was demonstrated on a two-dimensional test case representative of the heterogeneous material composition of the PUR-1 reactor core. A neural network implementation of the Kirchhoff-Helmholtz integral equation was employed to solve the boundary value problem using peripheral sensor measurements. The preliminary results confirm the strong potential of the proposed approach for accurate and minimally invasive neutron flux reconstruction.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Modular Framework for Modeling Hardware Elements in Distributed Engine Control Systems

Progress toward the implementation of distributed engine control in an aerospace application may be accelerated through the development of a hardware-in-the-loop (HIL) system for testing new control architectures and hardware outside of a physical test cell environment. One component required in an HIL simulation system is a high-fidelity model of the control platform: sensors, actuators, and the control law. The control system developed for the Commercial Modular Aero-Propulsion System Simulation 40k (40,000 pound force thrust) (C-MAPSS40k) provides a verifiable baseline for development of a model for simulating a distributed control architecture. This distributed controller model will contain enhanced hardware models, capturing the dynamics of the transducer and the effects of data processing, and a model of the controller network. A multilevel framework is presented that establishes three sets of interfaces in the control platform: communication with the engine (through sensors and actuators), communication between hardware and controller (over a network), and the physical connections within individual pieces of hardware. This introduces modularity at each level of the model, encouraging collaboration in the development and testing of various control schemes or hardware designs. At the hardware level, this modularity is leveraged through the creation of a Simulink (R) library containing blocks for constructing smart transducer models complying with the IEEE 1451 specification. These hardware models were incorporated in a distributed version of the baseline C-MAPSS40k controller and simulations were run to compare the performance of the two models. The overall tracking ability differed only due to quantization effects in the feedback measurements in the distributed controller. Additionally, it was also found that the added complexity of the smart transducer models did not prevent real-time operation of the distributed controller model, a requirement of an HIL system.

numerical simulation↗

Network device interface for digitally interfacing data channels to a controller a via network

The present invention provides a network device interface and method for digitally connecting a plurality of data channels to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. In one embodiment, the bus controller transmits messages to the network device interface containing a plurality of bits having a value defined by a transition between first and second states in the bits. The network device interface determines timing of the data sequence of the message and uses the determined timing to communicate with the bus controller.

Ellerbrock, Philip J.↗

Using Mesh Networking for A Dynamic Lunar Internet of Things (Liot)

The purpose of this project is to evaluate the feasibility of an IEEE 802.11 mesh protocol for lunar surface computing. This standard for wireless networking boosts speed, dependability and range of wireless transmissions. The concept is to integrate sensors (such as deployed science instruments) or Astronaut tools (such as a handheld spectrometer) that communicate with a node on a common cell. The nodes can extend the range of the cell and can dynamically reconfigure the data routing in case of another node failure. All of the data in a cell pass through a modem that communicates with a distant base station across a 4G link. The application of mesh networking to a potential lunar surface network increases robustness and fault tolerance over a traditional single-point modem system. By demonstrating the basic capability of a mesh network, the student team has learned about issues with power, distance, thermal, dust, radiation, data processing, and communication problems applicable to the lunar surface. This knowledge can feed into future NASA requirements to improve the capability of a LunaNET implementation for the Artemis program. This project follows 10 years of successful collaboration between NASA ARES, Texas Space, Technology, Applications and Research (T STAR) and Texas A&M University in a Public, Private, Academic (PPA) Partnership. NASA funds T STAR to mentor undergraduate Capstone teams in the College of Engineering Department to design, built, and test prototypes meeting NASA requirements. TAMU faculty lead the student teams in their academic class, and NASA Subject Matter Experts (SMEs) provide T STAR and students insight on requirements evolution, prior design projects, and future development goals.

Lunar Mesh Networking↗

Future Vision for Autonomous Ocean Observations

Autonomous platforms already make observations over a wide range of temporal and spatial scales, measuring salinity, temperature, nitrate, pressure, oxygen, biomass; and many other parameters. However, the observations are not comprehensive. Future autonomous systems need to be more affordable, more modular, more capable and easier to operate. Creative new types of platforms and new compact, low power, calibrated and stable sensors are under development to expand autonomous observations. Communications and recharging need bandwidth and power which can be supplied by standardized docking stations. In situ power generation will also extend endurance for many types of autonomous platforms, particularly autonomous surface vehicles. Standardized communications will improve ease of use, interoperability, and enable coordinated behaviors. Improved autonomy and communications will enable adaptive networks of autonomous platforms. Improvements in autonomy will have three aspects: hardware, control, and operations. As sensors and platforms have more onboard processing capability and energy capacity, more measurements become possible. Control systems and software will have the capability to address more complex states and sophisticated reactions to sensor inputs, which allows the platform to handle a wider variety of circumstances without direct operator control. Operational autonomy is increased by reducing operating costs. To maximize the potential of autonomous observations new standards and best practices are needed. In some applications, focus on common platforms and volume purchases could lead to significant cost reductions. Cost reductions could enable order-of-magnitude increases in platform operations and increase sampling resolution for a given level of investment. Energy harvesting technologies should be integral to the system design, for sensors, platforms, vehicles, and docking stations. Connections are needed between the marine energy and ocean observing communities to coordinate among funding sources, researchers, and end users. Regional teams should work with global organizations such as IOC/GOOS in governance development. International networks such as EGO for the emerging glider operations should also provide a forum for addressing governance. Networks of multiple vehicles can improve operational efficiencies and transform operational patterns. There is a need to develop operational architectures at regional and global scales to provide a backbone for active networking of autonomous platforms.

47 OTHER INSTRUMENTATION↗

Using Bayesian Networks for Candidate Generation in Consistency-based Diagnosis

Consistency-based diagnosis relies heavily on the assumption that discrepancies between model predictions and sensor observations can be detected accurately. When sources of uncertainty like sensor noise and model abstraction exist robust schemes have to be designed to make a binary decision on whether predictions are consistent with observations. This risks the occurrence of false alarms and missed alarms when an erroneous decision is made. Moreover when multiple sensors (with differing sensing properties) are available the degree of match between predictions and observations can be used to guide the search for fault candidates. In this paper we propose a novel approach to handle this problem using Bayesian networks. In the consistency- based diagnosis formulation, automatically generated Bayesian networks are used to encode a probabilistic measure of fit between predictions and observations. A Bayesian network inference algorithm is used to compute most probable fault candidates.

Narasimhan, Sriram↗

Optimal Power Flow With State Estimation in the Loop for Distribution Networks

Here in this article, we propose a framework for running optimal control-estimation synthesis in distribution networks. Our approach combines a primal-dual gradient-based optimal power flow solver with a state estimation feedback loop based on a limited set of sensors for system monitoring, instead of assuming exact knowledge of all states. The estimation algorithm reduces uncertainty on unmeasured grid states based on certain online state measurements and noisy "pseudomeasurements." We analyze the convergence of the proposed algorithm and quantify the statistical estimation errors based on a weighted least-squares estimator. The numerical results on a 4521-node network demonstrate that this approach can scale to extremely large networks and provide robustness to both large pseudomeasurement variability and inherent sensor measurement noise.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Radiation-Induced Noise Resilience of Neuromorphic Architectures

Neuromorphic event-based networks use asynchronous time-dependent information to extract features from input data that can allow for edge-based distributed applications such as object recognition. The noise resilience properties of such networks, especially in the context of space applications, are yet to be explored. In this paper, we use the hierarchy of time surfaces (HOTS) algorithm, which is one of the neuromorphic algorithms, to understand the least and most resilient modules in a neuromorphic network. The HOTS algorithm relies on the computing of time surfaces that maps the temporal delays between neighboring pixels into normalized features that involve many computations that are also found in other neuromorphic networks such as exponential decays, distance computations, etcetera. We implemented HOTS on a Digilent PYNQ board with a Xilinx Zynq 7020 system on a chip, and we subjected the boards running the HOTS network inference to neutron radiation at the Los Alamos Neutron Science Center. Furthermore, we used simulation models from our previous similar experiments on the event-based sensor to create a neutron induced noise model to quantify the effect of this noise on the overall performance of the network. This experiment provides the preliminary measurements of the reliability of the HOTS algorithm and proposes methods to create a more reliable HOTS architecture in future spacecraft missions.

Engineering↗

The Role of Advanced Information System Technology in Remote Sensing for NASA's Earth Science Enterprise in the 21st Century

Future NASA Earth observing satellites will carry high-precision instruments capable of producing large amounts of scientific data. The strategy will be to network these instrument-laden satellites into a web-like array of sensors to facilitate the collection, processing, transmission, storage, and distribution of data and data products - the essential elements of what we refer to as "Information Technology." Many of these Information Technologies will enable the satellite and ground information systems to function effectively in real-time, providing scientists with the capability of customizing data collection activities on a satellite or group of satellites directly from the ground. In future systems, extremely large quantities of data collected by scientific instruments will require the fastest processors, the highest communication channel transfer rates, and the largest data storage capacity to insure that data flows smoothly from the satellite-based instrument to the ground-based archive. Autonomous systems will control all essential processes and play a key role in coordinating the data flow through space-based communication networks. In this paper, we will discuss those critical information technologies for Earth observing satellites that will support the next generation of space-based scientific measurements of planet Earth, and insure that data and data products provided by these systems will be accessible to scientists and the user community in general.

Prescott, Glenn↗

Software Health Management with Bayesian Networks

Most modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.

Mengshoel, Ole↗

Classification of data patterns using an autoassociative neural network topology

A diagnostic expert system based on neural networks is developed and applied to the real-time diagnosis of jet and rocket engines. The expert system methodologies are based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. The approach addresses deficiencies inherent in many feedforward neural network models and greatly reduces the number of networks necessary to identify the existence of a fault condition and estimate the duration and severity of the identified fault. The network topology used in the present implementation of the diagnostic system is described, as well as the training regimen used and the response of the system to inputs representing both previously observed and unknown fault scenarios. Noise effects on the integrity of the diagnosis are also evaluated.

Dietz, W. E.↗

Two–Photon Printing of Shape–Memory Microstructures and Metasurfaces via Radical–Mediated Thiol–Vinyl Hydrothiolation

Shape-memory resists capable of high-resolution curing into arbitrarily designed structures are increasingly demanded for soft robotics, optical sensors, microscale manufacturing, and biomedicine. Amorphous, shape-memory thiol-vinyl networks were printed using two-photon polymerization (2PP) curing of a simple resin formulated with commercially available reagents. The ability to print high-resolution feature sizes down to 200 nm is attributed to the use of radicalmediated, thiol-vinyl step-growth polymerization that quickly crosslinks the resin, limiting diffusive transport. The thermomechanical behavior of the 2PP-cured material analyzed in compression, tension and three-point bending is similar to the behavior of the UV-polymerized samples. To demonstrate the ability to design, field, and test 4D responsive microstructures, an array of nine springs with coil diameters of 330 μm was printed. Following compressive shapefixing, printed arrays can release 11 μJ of stored elastic strain energy when reheated. Further, a new concept of dichroic-memory of a metamaterial device is demonstrated by printing a twisted woodpile structure with circular dichroism as characterized by Mueller Matrix ellipsometry. Furthermore, our results demonstrate how combining high-resolution 2PP curing with stimuli-responsive molecular architectures can further the engineering of responsive microstructures and metamaterials.

36 MATERIALS SCIENCE↗

Detector Interface for Streaming, Control, and Open-source integration (DISCO) v1.0.0

This suite consists of a multi-package ecosystem featuring detector emulators, EPICS areaDetector drivers, and remote server frameworks designed for the Advanced Light Source (ALS). Engineered for high-bandwidth devices—including VFCCD, Timepix3, Timepix4, and related pixel detectors—the software simulates hardware, wraps vendor SDKs into remote-callable servers, and integrates with open-source control systems. Key Capabilities: Distributed SDK Architecture: Server packages wrap hardware-specific SDKs, allowing areaDetector drivers to execute remote framework calls. This isolates proprietary libraries from the EPICS IOC, enhancing stability and enabling distributed computing across beamline networks. Device Support: Custom drivers for VFCCD, the Timepix family, and similar sensors optimize the data path from hardware control to high-speed transport. Full-Stack Emulation: Sophisticated emulator packages allow end-to-end pipeline testing and software development without requiring physical hardware or beam time. Integrated Workflows: Supports high-bandwidth streaming for real-time analysis and robust, metadata-rich file-based workflows (e.g., HDF5/NeXus). By standardizing interfaces across heterogeneous hardware, this suite reduces technical debt. It provides the ALS with a scalable, open-source solution to manage massive data rates within a unified control environment.

Mahl, Johannes [Lawrence Berkeley National Laborat↗

Integrated Controls Package for High Performance Interior Retrofit [Slides]

For the last few years, networked lighting control (NLCs) have promised significant energy savings beyond what is achieved through a basic light-emitting diode (LED) lighting retrofit. At the same time, NLCs can substantially increase the cost and complexity of the lighting retrofit. And as lighting system wattage declines because of the increasing efficiency of LEDs, advanced controls have less lighting energy to save and the cost-effectiveness of the NLC investment decreases. But NLCs can be leveraged to achieve significant energy savings and value by enhancing control of other building systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Earth orbit navigation study. Volume 2: System evaluation

An overall systems evaluation was made of five candidate navigation systems in support of earth orbit missions. The five systems were horizon sensor system, unkown landmark tracking system, ground transponder system, manned space flight network, and tracking and data relay satellite system. Two reference missions were chosen: a low earth orbit mission and a transfer trajectory mission from low earth orbit to geosynchronous orbit. The specific areas addressed in the evaluation were performance, multifunction utilization, system mechanization, and cost.

Source record↗

User data dissemination concepts for earth resources: Executive summary

The impact of the future capabilities of earth-resources data sensors (both satellite and airborne) and their requirements on the data dissemination network were investigated and optimum ways of configuring this network were determined. The scope of this study was limited to the continental U.S.A. (including Alaska) and to the 1985-1995 time period. Some of the conclusions and recommendations reached were: (1) Data from satellites in sun-synchronous polar orbits (700-920 km) will generate most of the earth-resources data in the specified time period. (2) Data from aircraft and shuttle sorties cannot be readily integrated in a data-dissemination network unless already preprocessed in a digitized form to a standard geometric coordinate system. (3) Data transmission between readout stations and central preprocessing facilities, and between processing facilities and user facilities are most economically performed by domestic communication satellites. (4) The effect of the following factors should be studied: cloud cover, expanded coverage, pricing strategies, multidiscipline missions.

Davies, R.↗