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At least 667 records · Page 37

Performance of a Permanent-Magnet Cylindrical Hall-Effect Thruster

The performance of a low-power cylindrical Hall thruster, which more readily lends itself to miniaturization and low-power operation than a conventional (annular) Hall thruster, was measured using a planar plasma probe and a thrust stand. The field in the cylindrical thruster was produced using permanent magnets, promising a power reduction over previous cylindrical thruster iterations that employed electromagnets to generate the required magnetic field topology. Two sets of ring-shaped permanent magnets are used, and two different field configurations can be produced by reorienting the poles of one magnet relative to the other. A plasma probe measuring ion flux in the plume is used to estimate the current utilization for the two magnetic topologies. The measurements indicate that electron transport is impeded much more effectively in one configuration, implying higher thrust efficiency. Thruster performance measurements on this configuration were obtained over a power range of 70-350 W and with the cathode orifice located at three different axial positions relative to the thruster exit plane. The thrust levels over this power range were 1.25-6.5 mN, with anode efficiencies and specific impulses spanning 4-21% and 400-1950 s, respectively. The anode efficiency of the permanent-magnet thruster compares favorable with the efficiency of the electromagnet thruster when the power consumed by the electromagnets is taken into account.

Polzin, K. A.↗

Self-Sensing, Stretchable, Active Circuit Arrays: Liquid Metal Paste as a Combination Interconnect and Strain Sensor

Stretchable electrical interconnects and substrate materials are increasingly used to create flexible and con-formable electronic systems for soft robotics, smart textiles, and wearable devices. Wires fabricated using composite or liquid conductive inks encapsulated in silicone enable high strain and are mechanically robust. The resistance of these inter-connects increases with strain, which can present challenges for power delivery and signaling among electronic components. However, this effect can be used directly to estimate strain within a stretchable circuit without the need for additional sensor components. In this work, we present an approach for fabricating fully-stretchable, multi-layer active circuit arrays in silicone using liquid metal paste interconnects, in which power and data wires are re-purposed as strain sensors to estimate substrate deformation. As a proof-of-principle, we demonstrate a 3×3 active circuit array that self-senses relative voltage supply at each node to estimate deformation and consumes less than 10 mA per node. Each node is digitally addressable and performs both analog measurement and digital conversion. All interconnects are fabricated using liquid metal paste, and power, data, and sensing are performed over a shared, four-wire interface in this multi-layer stretchable printed circuit board.

99 GENERAL AND MISCELLANEOUS↗

Superconducting Radio-frequency Cavity Fault Classification Using Machine Learning at Jefferson Laboratory

We report on the development of machine learning models for classifying C100 superconducting radiofrequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. Of the 418 SRF cavities in CEBAF, 96 are designed with a digital low-level RF system configured such that a cavity fault triggers recordings of RF signals for each of eight cavities in the cryomodule. Subject matter experts analyze the collected time-series data and identify which of the eight cavities faulted first and classify the type of fault. This information is used to find trends and strategically deploy mitigations to problematic cryomodules. However, manually labeling the data is laborious and time-consuming. By leveraging machine learning, near real-time - rather than postmortem - identification of the offending cavity and classification of the fault type has been implemented. We discuss the performance of the machine learning models during a recent physics run. We also discuss efforts for further insights into fault types through unsupervised learning techniques and present preliminary work on cavity and fault prediction using data collected prior to a failure event.

Tennant, C. D.↗

High efficiency turbine blade coatings

The development of advanced thermal barrier coatings (TBCs) of yttria stabilized zirconia (YSZ) that exhibit lower thermal conductivity through better control of electron beam - physical vapor deposition (EB-PVD) processing is of prime interest to both the aerospace and power industries. This report summarizes the work performed under a two-year Lab-Directed Research and Development (LDRD) project (38664) to produce lower thermal conductivity, graded-layer thermal barrier coatings for turbine blades in an effort to increase the efficiency of high temperature gas turbines. This project was sponsored by the Nuclear Fuel Cycle Investment Area. Therefore, particular importance was given to the processing of the large blades required for industrial gas turbines proposed for use in the Brayton cycle of nuclear plants powered by high temperature gas-cooled reactors (HTGRs). During this modest (~1 full-time equivalent (FTE)) project, the processing technology was developed to create graded TBCs by coupling ion beam-assisted deposition (IBAD) with substrate pivoting in the alumina-YSZ system. The Electron Beam - 1200 kW (EB-1200) PVD system was used to deposit a variety of TBC coatings with micron layered microstructures and reduced thermal conductivity below 1.5 W/m.K. The use of IBAD produced fully stoichiometric coatings at a reduced substrate temperature of 600°C and a reduced oxygen background pressure of 0.1 Pa. IBAD was also used to successfully demonstrate the transitioning of amorphous PVD-deposited alumina to the -phase alumina required as an oxygen diffusion barrier and for good adhesion to the substrate Ni 2 Al 3 bondcoat. This process replaces the time consuming thermally grown oxide formation required before the YSZ deposition. In addition to the process technology, Direct Simulation Monte Carlo plume modeling and spectroscopic characterization of the PVD plumes were performed. The project consisted of five tasks. These included the production of layered periodic microstructures in the coating, the Direct Simulation Monte Carlo (DSMC) modeling of particle transport in the PVD plume, functional graded layer development, the deposition of all layers to form a complete coating, and materials characterization including thermal testing. Ion beam-assisted deposition, beam sharing through advanced digital rastering, substrate pivoting, hearth calorimetry, infrared imaging, fiber optic-enabled optical emission spectroscopy and careful thermal management were used to achieve all the milestones outlined in the FY 02 LDRD proposal.

36 MATERIALS SCIENCE↗

Defluorination Mechanisms and Real-Time Dynamics of Per- and Polyfluoroalkyl Substances on Electrified Surfaces

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants found in groundwater sources and a wide variety of consumer products. In recent years, electrochemical approaches for the degradation of these harmful contaminants have garnered a significant amount of attention due to their efficiency and chemical-free modular nature. However, these electrochemical processes occur in open, highly non-equilibrium systems, and a detailed understanding of PFAS degradation mechanisms in these promising technologies is still in its infancy. To shed mechanistic insight into these complex processes, we present the first constant-electrode potential (CEP) quantum calculations of PFAS degradation on electrified surfaces. These advanced CEP calculations provide new mechanistic details about the intricate electronic processes that occur during PFAS degradation in the presence of an electrochemical bias, which cannot be gleaned from conventional density functional theory calculations. We complement our CEP calculations with large-scale ab initio molecular dynamics simulations in the presence of an electrochemical bias to provide time scales for PFAS degradation on electrified surfaces. Taken together, our CEP-based quantum calculations provide critical reaction mechanisms for PFAS degradation in open electrochemical systems, which can be used to prescreen candidate material surfaces and optimal electrochemical conditions for remediating PFAS and other environmental contaminants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atmospheric pressure plasma functionalization of polystyrene

Atmospheric pressure plasma jets (APPJs) are used to improve the adhesive and hydrophilic properties of commodity hydrocarbon polymers such as polypropylene, polyethylene, and polystyrene (PS). These improvements largely result from adding oxygen functional groups to the surface. PS functionalization is of interest to produce high value biocompatible well-plates and dishes, which require precise control over surface properties. In this paper, we discuss results from a computational investigation of APPJ functionalization of PS surfaces using He/O 2 /H 2 O gas mixtures. A newly developed surface reaction mechanism for functionalization of PS upon exposure to these plasmas is discussed. A global plasma model operated in plug-flow mode was used to predict plasma-produced species fluxes onto the PS surface. A surface site balance model was used to predict oxygen-functionalization of the PS following exposure to the plasma and ambient air. We found that O-occupancy on the surface strongly correlates with the O-atom flux to the PS, with alcohol groups and cross-linked products making the largest contributors to total oxygen fraction. Free radical sites, such as alkoxy and peroxy, are quickly consumed in the post-plasma exposure to air through passivation and cross-linking. O-atom fluences approaching 10 17 cm -2 saturate the O-occupancy on the PS surface, creating functionality that is not particularly sensitive to moderate changes in operating conditions.

36 MATERIALS SCIENCE↗

Machine Learning Based Cavity Fault Classification and Prediction

We report on the development of machine learning models for classifying C100 superconducting radio frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a continuous-wave recirculating linac utilizing 418 SRF cavities to accelerate electrons up to 12 GeV through 5-passes. Of these, 96 cavities (12 cryomodules) are designed with a digital low-level RF system configured such that a cavity fault triggers waveform recordings of 17 RF signals for each of the eight cavities in the cryomodule. Subject matter experts (SME) can analyze the collected time-series data, identify which of the eight cavities faulted first, and classify the type of fault. This information is used to find trends and strategically deploy mitigations to problematic cryomodules. However, manually labeling the data is laborious and time-consuming. By leveraging machine learning, near real-time – rather than post-mortem – identification of the offending cavity and classification of the fault type has been implemented. We discuss the performance of the ML models during a recent physics run.

43 PARTICLE ACCELERATORS↗

Digital Radar-Signal Processors Implemented in FPGAs

High-performance digital electronic circuits for onboard processing of return signals in an airborne precipitation- measuring radar system have been implemented in commercially available field-programmable gate arrays (FPGAs). Previously, it was standard practice to downlink the radar-return data to a ground station for postprocessing a costly practice that prevents the nearly-real-time use of the data for automated targeting. In principle, the onboard processing could be performed by a system of about 20 personal- computer-type microprocessors; relative to such a system, the present FPGA-based processor is much smaller and consumes much less power. Alternatively, the onboard processing could be performed by an application-specific integrated circuit (ASIC), but in comparison with an ASIC implementation, the present FPGA implementation offers the advantages of (1) greater flexibility for research applications like the present one and (2) lower cost in the small production volumes typical of research applications. The generation and processing of signals in the airborne precipitation measuring radar system in question involves the following especially notable steps: The system utilizes a total of four channels two carrier frequencies and two polarizations at each frequency. The system uses pulse compression: that is, the transmitted pulse is spread out in time and the received echo of the pulse is processed with a matched filter to despread it. The return signal is band-limited and digitally demodulated to a complex baseband signal that, for each pulse, comprises a large number of samples. Each complex pair of samples (denoted a range gate in radar terminology) is associated with a numerical index that corresponds to a specific time offset from the beginning of the radar pulse, so that each such pair represents the energy reflected from a specific range. This energy and the average echo power are computed. The phase of each range bin is compared to the previous echo by complex conjugate multiplication to obtain the mean Doppler shift (and hence the mean and variance of the velocity of precipitation) of the echo at that range.

Berkun, Andrew↗

Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopy

Tropical forests are one of the main carbon sinks on Earth, but the magnitude of CO 2 absorbed by tropical vegetation remains uncertain. Terrestrial biosphere models (TBMs) are commonly used to estimate the CO 2 absorbed by forests, but their performance is highly sensitive to the parameterization of processes that control leaf-level CO 2 exchange. Direct measurements of leaf respiratory and photosynthetic traits that determine vegetation CO 2 fluxes are critical, but traditional approaches are time-consuming. Reflectance spectroscopy can be a viable alternative for the estimation of these traits and, because data collection is markedly quicker than traditional gas exchange, the approach can enable the rapid assembly of large datasets. However, the application of spectroscopy to estimate photosynthetic traits across a wide range of tropical species, leaf ages and light environments has not been extensively studied. Here, we used leaf reflectance spectroscopy together with partial least-squares regression (PLSR) modeling to estimate leaf respiration ( R dark25 ), the maximum rate of carboxylation by the enzyme Rubisco ( V cmax25 ), the maximum rate of electron transport ( J max25 ), and the triose phosphate utilization rate ( T p25 ), all normalized to 25°C. We collected data from three tropical forest sites and included leaves from fifty-three species sampled at different leaf phenological stages and different leaf light environments. Our resulting spectra-trait models validated on randomly sampled data showed good predictive performance for V cmax25 , J max25 , T p25 and R dark25 (RMSE of 13, 20, 1.5 and 0.3 μmol m -2 s -1 , and R 2 of 0.74, 0.73, 0.64 and 0.58, respectively). The models showed similar performance when applied to leaves of species not included in the training dataset, illustrating that the approach is robust for capturing the main axes of trait variation in tropical species. We discuss the utility of the spectra-trait and traditional gas exchange approaches for enhancing tropical plant trait studies and improving the parameterization of TBMs.

54 ENVIRONMENTAL SCIENCES↗

Aromatic graphene

In recent years graphene attracts the scientific and engineering communities due to its outstanding electronic, thermal, mechanical and optical properties and many potential applications. Recently, Popov et al. [1] have studied the properties of graphene and proved that it is aromatic but without fragrance. In this paper, we present a theory to prepare graphene with fragrance. This can be used as scented pencils, perfumes, room and car fresheners, cosmetics and many other useful household substances.

36 MATERIALS SCIENCE↗

Challenges, Industry Practice, and Research Opportunities for Protection of IBR-Rich Systems

The objective of this technical report is to outline the challenges of protection design for power systems rich in inverter-based resources (IBRs), synthesize current industrial practices, review new approaches from recent literature, and explore future opportunities in protection. IBRs are experiencing widespread adoption across both transmission and distribution systems. When present in significant quantities, IBRs challenge the performance of many traditional protection functions. To address these issues, the industry has developed sophisticated protection schemes that involve advanced relaying techniques in highly engineered pilot projects. However, these schemes are expensive and time-consuming to develop, build, and test. Researchers have proposed a number of new approaches for protection in IBR-rich distribution systems. Despite their potential, these new approaches do not address some major shortcomings of industry approaches stemming from complexity, practical requirements, and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Runtime performance of a GAMESS quantum chemistry application offloaded to GPUs

Summary Computational chemistry is at the forefront of solving urgent societal problems, such as polymer upcycling and carbon capture. The complexity of modeling these processes at appropriate length and time scales is mainly manifested in the number and types of chemical species involved in the reactions and may require models of several thousand atoms and large basis sets to accurately capture the chemical complexity and heterogeneity in the physical and chemical processes. The quantum chemistry package General Atomic and Molecular Electronic Structure System (GAMESS) has a wide array of methods that can efficiently and accurately treat complex chemical systems. In this work, we have used the GAMESS Effective Fragment Molecule Orbital (EFMO) method for electronic structure calculation of a challenging mesoporous silica nanoparticle (MSN) model surrounded by about 4700 water molecules to investigate the strong scaling and GPU offloading on hybrid CPU‐GPU nodes. Experiments were performed on the Perlmutter platform at the National Energy Research Scientific Computing Center. Good strong scaling and load balancing have been observed on up to 88 hybrid nodes for different settings of the execution parameters for the calculation considered here. When GPUs are oversubscribed by offloading work from multiple CPU processes, using the NVIDIA multi‐process service (MPS) has consistently reduced time to solution and energy consumed. Additionally, for some configuration parameter settings, oversubscription with MPS improved performance by up to 5.8% over the case without oversubscription.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Functional materials and devices by self-assembly

The field of self-assembly has moved far beyond early work, where the focus was primarily the resultant beautiful two- and three-dimensional structures, to a focus on forming materials and devices with important properties either otherwise not available, or only available at great cost. Over the last few years, materials with unprecedented electronic, photonic, energy-storage, and chemical separation functionalities were created with self-assembly, while at the same time, the ability to form even more complex structures in two and three dimensions has only continued to advance. Self-assembly crosscuts all areas of materials. Functional structures have now been realized in polymer, ceramic, metallic, and semiconducting systems, as well as composites containing multiple classes of materials. Finally, as the field of self-assembly continues to advance, the number of highly functional systems will only continue to grow and make increasingly greater impacts in both the consumer and industrial space.

Materials for Devices↗

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of origin. This information is subsequently utilized to identify failure trends and to implement corrective measures on the offending cavity. Manual inspection of large-scale, time-series data, generated by frequent system failures is tedious and time consuming, and thereby motivates the use of machine learning (ML) to automate the task. This study extends work on a previously developed system based on traditional ML methods (Tennant and Carpenter and Powers and Shabalina Solopova and Vidyaratne and Iftekharuddin, Phys. Rev. Accel. Beams, 2020, 23, 114601), and investigates the effectiveness of deep learning approaches. The transition to a DL model is driven by the goal of developing a system with sufficiently fast inference that it could be used to predict a fault event and take actionable information before the onset (on the order of a few hundred milliseconds). Because features are learned, rather than explicitly computed, DL offers a potential advantage over traditional ML. Specifically, two seminal DL architecture types are explored: deep recurrent neural networks (RNN) and deep convolutional neural networks (CNN). We provide a detailed analysis on the performance of individual models using an RF waveform dataset built from past operational runs of CEBAF. In particular, the performance of RNN models incorporating long short-term memory (LSTM) are analyzed along with the CNN performance. Furthermore, comparing these DL models with a state-of-the-art fault ML model shows that DL architectures obtain similar performance for cavity identification, do not perform quite as well for fault classification, but provide an advantage in inference speed.

97 MATHEMATICS AND COMPUTING↗

Investigating the Effects of Pin Tool Design on Friction Stir Welded Ti-6Al-4V

Friction stir welding (FSWing), a solid state joining technique, uses a non-consumable rotating pin tool to thermomechanically join materials. Heating of the weldment caused by friction and deformation is a function of the interaction between the pin tool and the work piece. Therefore, the geometry of the pin tool is in part responsible for the resulting microstructure and mechanical properties. In this study microwave sintered tungsten carbide (WC) pin tools with tapers and flats were used to FSW Ti-6Al-4V. Transverse sections of welds were mechanically tested, and the microstructure was characterized using optical microscopy (OM) and scanning election microscopy (SEM). X-ray diffraction (XRD) and electron back-scatter diffraction (EBSD) were used to characterize the texture within the welds produced from the different pin tool designs.

Rubisoff, H. A.↗

Development of Corrosion Resistant Coatings for Structural Materials for Liquid Fueled Molten Salts Reactors Applications (Final Report)

Current structural alloys, code certified for the MSRs temperature ranges, contain high levels of chromium, making them highly susceptible to molten halide salt corrosion. One potential solution to circumvent the need for code certification of novel alloys, which is expensive and time consuming, is to design claddings that will protect the underlying code certified materials from corrosion damage during operation. In this work, we examined the corrosion of Ni and Cu electroplated, Ni and CuNi weld overlay, Mo-laser clad, and carburized claddings on SS316H for use in molten salt reactor environments. After characterization of the cladded materials (Task 1), static corrosion tests were used to assess corrosion resistance of the claddings in typical molten fluoride salts (Task 2). The corrosion tests were performed in molten FLiNaK at 700°C up to 1000 hours. Pre- and post-corrosion Scanning Electron Microscopy (SEM), energy-dispersive-spectroscopy (EDS), Transmission Electron Microscopy (TEM), X-ray Diffraction (XRD) and glow-discharge-optical-emission-spectroscopy (GDOES) were performed on cladding cross-sections and surfaces to evaluate degradation. The Cu and Ni electroplated samples, as well as the carburized samples, showed excellent corrosion resistance relative to the bare SS316H. To assess high temperature cladding stability, ageing experiments were performed at temperatures up to 900 C in inert atmosphere for the electroplated and carburized samples and a diffusion model was developed to predict long term cladding behavior (Task 3). It was found that the Cu cladding was basically insensitive to the high temperature ageing, except for small secondary phases forming at the interface. On the other hand, the Ni electroplated cladding experienced significant interdiffusion. Nevertheless, the gain in corrosion resistance for a 100μm Ni electroplated cladding is phenomenal, with more than 50% reduction in chromium dissolution from the substrate material for the first 15 years of salt exposure at 700°C. To assess radiation resistance and phase stability, high-temperature 4MeV Ni heavy ion irradiation was performed across the cladding/substrate interface up to 50 displacement-per-atom (DPA) at 500°C and 700°C to assess the phase stability and irradiation behaviors of the electroplated systems (Task 4). The Ni and Cu electroplated systems did not experience void swelling at the contrary to the SS316H substrate due to their nanocrystalline nature. Some level of recrystallization was observed in the cladding, as well as radiation induced segregation and enhanced diffusion. The interface acted as a potent sink for point defects with the presence of a void denuded zone. The mechanical properties of the claddings were assessed using thermal shock, micro-indentation, nano-indentation, and four-point bend testing experiments (Task 5). These experiments were performed on the claddings in as-received, corroded, irradiated, and thermally aged states to determine the effects of typical molten salt reactor environments on cladding integrity. No significant mass loss was observed after repeated thermal shocks. While the electroplated samples softened after high-temperature ageing, irradiation hardening compensate this effect, such that there is little different with the as-received materials. The results of these experiments suggest that the electroplated (copper/nickel) show the greatest promise for application in molten salt reactor development. These claddings prevented any chromium dissolution from occurring during the static corrosion experiments. Additionally, they demonstrated favorable properties for high temperature diffusion, phase stability, interfacial mechanical properties, and irradiation resistance. Weld-overlay cladding are also of great interest and could reach properties similar to the electroplated samples upon optimization (especially with multiple weld passes). The carburized SS316H showed excellent behavior as well, but more work needs to be done to assess their long-term stability. Finally, the Mo-laser clad system was not pursued further due to the manufacturing challenges. It is also worth noting that the Ni cladding systems should behave relatively well in terms of weldability since the Ni-weld overlay microstructure and associated corrosion rate are sound. While the NiCu weld-overlay has even lower corrosion rates than the Ni-weld overlay, more studies on welding of Cu-electroplated systems are necessary since Cu clusters are known to embrittle steels.

36 MATERIALS SCIENCE↗

Low-Thermal-Conductivity Pyrochlore Oxide Materials Developed for Advanced Thermal Barrier Coatings

When turbine engines operate at higher temperatures, they consume less fuel, have higher efficiencies, and have lower emissions. The upper-use temperatures of the base materials (superalloys, silicon-based ceramics, etc.) used for the hot-section components of turbine engines are limited by the physical, mechanical, and corrosion characteristics of these materials. Thermal barrier coatings (TBCs) are applied as thin layers on the surfaces of these materials to further increase the operating temperatures. The current state-of-the-art TBC material in commercial use is partially yttria-stabilized zirconia (YSZ), which is applied on engine components by plasma spraying or by electron-beam physical vapor deposition. At temperatures higher than 1000 C, YSZ layers are prone to sintering, which increases thermal conductivity and makes them less effective. The sintered and densified coatings can also reduce thermal stress and strain tolerance, which can reduce the coating s durability significantly. Alternate TBC materials with lower thermal conductivity and better sintering resistance are needed to further increase the operating temperature of turbine engines.

Bansal, Narottam P.↗

GPM Mission's Best Practices: PERP

Similar to other missions, the Global Precipitation Measurement (GPM) Core Observatory's Command and Data Handling (C&DH) subsystem is critical for operations of the spacecraft. The onboard C&DH system comprises of two fully redundant boxes - a primary and a cold backup. Within each box, amongst other components, is a Single Board Computer (SBC) that hosts the flight software (FSW) system. In the event of an SBC reset, the Flight Operations Team (FOT) is poised with a lengthy task of restoring the SBC to nominal configuration. Due to the complexity of the C&DH system, this may take many days at a time to complete. The spacecraft's FSW applications are located in Electronically Erasable Programmable Read-Only Memory (EEPROM) and are copied into Random Access Memory (RAM) upon SBC initialization/reset. Each SBC has two banks of EEPROM, with each bank containing a copy of the FSW. Since launch, there have been many configuration changes to tables and applications that have been loaded into just RAM. Unfortunately, these changes are vulnerable to being wiped during a SBC initialization/reset, when the RAM is overwritten by the EEPROM. Although the EEPROM loads the default FSW configurations, the process to command non-default individual table and application changes is very cumbersome and time consuming. This consequentially increases the time until the spacecraft is back into nominal Mission Science Mode (MSM) drastically. The GPM Power-On Reset (POR) Expedited Recovery Process (PERP) Design introduces a method of consolidating commands into a single file load which the SBC can process independently of the ground - decreasing recovery time, the level of TDRS support reliance, and human error. This tested design can be implemented across many other missions that utilize a similar core Flight Executive (cFE) platform; hence providing an easy-to-follow, safe, and efficient process that can be applied across the board.

recovery↗