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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,477 records · Page 82

GPAW: An open Python package for electronic structure calculations

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe–Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn–Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interfacial defect reduction enhances universal power law response in Mo–SiNx granular metals

Granular metals (GMs), consisting of metal nanoparticles separated by an insulating matrix, frequently serve as a platform for fundamental electron transport studies. However, few technologically mature devices incorporating GMs have been realized, in large part because intrinsic defects (e.g., electron trapping sites and metal/insulator interfacial defects) frequently impede electron transport, particularly in GMs that do not contain noble metals. Here, we demonstrate that such defects can be minimized in molybdenum–silicon nitride (Mo–SiN x ) GMs via optimization of the sputter deposition atmosphere. For Mo–SiN x GMs deposited in a mixed Ar/N 2 environment, x-ray photoemission spectroscopy shows a 40%–60% reduction of interfacial Mo-silicide defects compared to Mo–SiN x GMs sputtered in a pure Ar environment. Electron transport measurements confirm the reduced defect density; the dc conductivity improved (decreased) by 10 4 –10 5 and the activation energy for variable-range hopping increased 10×. Since GMs are disordered materials, the GM nanostructure should, theoretically, support a universal power law (UPL) response; in practice, that response is generally overwhelmed by resistive (defective) transport. Here, the defect-minimized Mo–SiN x GMs display a superlinear UPL response, which we quantify as the ratio of the conductivity at 1 MHz to that at dc, Δσ ω ⁠. Remarkably, these GMs display a Δσ ω up to 10 7 , a three-orders-of-magnitude improved response than previously reported for GMs. By enabling high-performance electric transport with a non-noble metal GM, this work represents an important step toward both new fundamental UPL research and scalable, mature GM device applications.

36 MATERIALS SCIENCE↗

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗

Evaluating Unified Memory Performance in HIP

Heterogeneous unified memory management between a CPU and a GPU is a major challenge in GPU computing. Recently, unified memory (UM) has been supported by software and hardware components on AMD computing platforms. The support could simplify the complexities of memory management. In this paper, we attempt to have a better understanding of UM by evaluating the performance of UM programs on an AMD MI100 GPU. More specifically, we evaluate data migration using UM against other data transfer techniques for the overall performance of an application, assess the impacts of three commonly used optimization techniques on the kernel execution time of a vector add sample, and compare the performance and productivity of selected benchmarks with and without UM. The performance overhead associated with UM is not trivial, but it can improve programming productivity by reducing lines of code for scientific applications. We aim to present early results and feedback on the UM performance to the vendor.

Jin, Zheming↗

Rapid Carbon Fiber Prepreg Molding Technology for Automobile Structural Parts - "SEAHAWKS"

Carbon fiber reinforced plastics (CFRP) offer a variety of potential benefits to automotive parts vs. metals, mainly in the form of light-weighting, part consolidation, and corrosion resistance. However, complexities of composite manufacturing and lack of robust supply chain evolution and integration have hindered technological advancements to overcome high manufacturing costs, slow production rates and prolonged time to market. As a result, the use of CFRP in automotive structural parts has been limited to expensive “low to medium” volume platforms. The project overall investigates a concept of ecosystem-based composite manufacturing that enables rapid implementation of an integrated manufacturing system. Through partnering with individual organizations in the prepreg supply chain along with their respective technological advancements in materials, part designs, tool, equipment, recycling and repair, this project’s objective is to integrate these technologies into a manufacturing system through optimizing them individually and as a whole. Upon a successful delivery of a finished composite component to market, all associated technologies are evolved to production readiness levels not only individually but also in part of the integrated manufacturing system itself. Risks are mitigated effectively, as development costs and successes (and/or failures) are shared among all organizations. As a result, further cost reduction of the finished component is anticipated. Toray Composites (America) Inc. led the effort along with 13 other organizations to investigate and validate the concept. Phase I of this project via flat panel demonstrations focused on molding aspects of the integrated manufacturing system from several combinations of prepreg materials and molding methods used such as hydraulic press, RapidClave®, heated composite light tool (HCLT), light induction tool (LIT) and Quickstep. Other aspects such as automation equipment, recycling and component identification to further investigate and validate the concept via component demonstration in Phase II were also explored. It was found that several prepreg/process combinations could achieve a 3-6 min cure cycle time with panel thickness from 0.8 to 2.4 mm. This can be achieved under compaction pressure as low as vacuum, leading to composite panels that are void free, have good to excellent molded surfaces, Tg (by G’onset of DMA) ranging from 120-190 °C, and mechanical performance comparable to conventional autoclave cure.

36 MATERIALS SCIENCE↗

ARCUS Vertical-Axis Wind Turbine (Final Scientific/Technical Report)

While land-based wind energy has become economically competitive with traditional energy generation sources in the U.S., offshore wind is not. For floating offshore wind this difference is even more substantial where the levelized cost of energy (LCOE) is projected to be around 3-5 times more expensive than land-based wind. The turbine capital costs represent around 50% of the LCOE for land-based wind sites, but the increased system costs for floating offshore wind reduce this to 20%. The platform and mooring costs are the single largest contributor to the LCOE for floating offshore wind where their mass must counteract the overturning moment caused by the turbine’s thrust force. Despite the high costs of the platform and relatively low cost of the turbine, current offshore wind turbines are designed essentially the same as for land-based sites. Reducing the LCOE is the greatest challenge to realize the benefits of sustained development of floating offshore wind in the U.S. Reducing the complicated system costs of floating offshore wind will enable the industry to continue to grow and outpace current projections if reduced cost curves can be reached. The ideal wind energy system would remove all mass and cost that is not directly capturing energy from the wind. For floating offshore wind energy systems, this objective is even more significant as increased mass above the water level must be supported by larger and more expensive floating platforms. For this reason, vertical-axis wind turbines (VAWTs) are ideal for floating offshore sites and have several advantages over horizontal-axis wind turbines (HAWTs) at this scale. Large VAWTs offer opportunities for improved energy capture over HAWTs as single units and with reduced wind plant aerodynamic losses through enhanced wake recovery. Additionally, the platform-level placement of the VAWT drivetrain greatly reduces the demands placed on the floating platform and its mass and cost. The ARCUS vertical-axis wind turbine concept (U.S. 11,421,650 B2) is an iteration beyond traditional Darrieus-type VAWTs that replaces the rigid tower with blades that are bent into shape and held in place with tensioned center supports, like a bow. The ARCUS design has been shown to further decrease the VAWT rotor mass properties, with a 50% reduction over traditional Darrieus VAWTs quantified in the ATLANTIS program. The ARCUS VAWT’s efficient use of material for the rotor and turbine support structures combined with its lowered center of gravity enables a tension-leg platform (TLP) with simplified installation procedures. TLPs have been an emerging platform architecture in the Oil and Gas industry and demonstrated to have the lowest hull mass requirements while maintaining stability with minimal roll and pitch deflections in operation. A 22 MW ARCUS turbine has been designed with a three-column TLP that enables quayside integration of the turbine while maintaining system stability during tow-out and installation and having optimal mass and cost properties. A comprehensive analysis shows the optimal ARCUS TLP system design minimizes LCOE through efficient material usage and increased energy capture to yield a competitive LCOE estimate of $\$$55/MWh. A comparison with a reference HAWT, having the same swept area, quantifies the advantages that helped to produce this improved LCOE for the ARCUS concept: (1) 30% reduction in total turbine mass, (2) 70% reduction in turbine center of gravity, and (3) 45% increase in energy production over what is optimal for a HAWT. Intellectual property has been generated through the ATLANTIS program providing opportunities to further reduce the LCOE and improve the performance of the ARCUS turbine and TLP system, expanding the list of innovations to support commercial development of the ARCUS concept.

17 WIND ENERGY↗

Doppler lidar wind measurement on Eos

A polar-orbiting platform segment of the Earth Observing System (EOS) could carry a CO2-laser based Doppler lidar for recording global wind profiles. Development goals would include the manufacture of a 10 J laser with a 2 yr operational life, space-rating the optics and associated software, and the definition of models for global aerosol distributions. Techniques will be needed for optimal scanning and generating computer simulations which will provide adequately accurate weather predictions.

Fitzjarrald, D.↗

Array-Pattern-Match Compiler for Opportunistic Data Analysis

A computer program has been written to facilitate real-time sifting of scientific data as they are acquired to find data patterns deemed to warrant further analysis. The patterns in question are of a type denoted array patterns, which are specified by nested parenthetical expressions. [One example of an array pattern is ((>3) 0 (not=1)): this pattern matches a vector of at least three elements, the first of which exceeds 3, the second of which is 0, and the third of which does not equal 1.] This program accepts a high-level description of a static array pattern and compiles a highly optimal and compact other program to determine whether any given instance of any data array matches that pattern. The compiler implemented by this program is independent of the target language, so that as new languages are used to write code that processes scientific data, they can easily be adapted to this compiler. This program runs on a variety of different computing platforms. It must be run in conjunction with any one of a number of Lisp compilers that are available commercially or as shareware.

James, Mark↗

Remote Sensing of Precipitation from Airborne and Spaceborne Radar

Weather radar measurements from airborne or satellite platforms can be an effective remote sensing tool for examining the three-dimensional structures of clouds and precipitation. This chapter describes some fundamental properties of radar measurements and their dependence on the particle size distribution (PSD) and radar frequency. The inverse problem of solving for the vertical profile of PSD from a profile of measured reflectivity is stated as an optimal estimation problem for single- and multi-frequency measurements. Phenomena that can change the measured reflectivity Z(sub m) from its intrinsic value Z(sub e), namely attenuation, non-uniform beam filling, and multiple scattering, are described and mitigation of these effects in the context of the optimal estimation framework is discussed. Finally, some techniques involving the use of passive microwave measurements to further constrain the retrieval of the PSD are presented.

cloud↗

Prototyping Operational Autonomy for Space Traffic Management

Current state of the art in Space Traffic Management (STM) relies on a handful of providers for surveillance and collision prediction, and manual coordination between operators. Neither is scalable to support the expected 10x increase in spacecraft population in less than 10 years, nor does it support automated manuever planning. We present a software prototype of an STM architecture based on open Application Programming Interfaces (APIs), drawing on previous work by NASA to develop an architecture for low-altitude Unmanned Aerial System Traffic Management. The STM architecture is designed to provide structure to the interactions between spacecraft operators, various regulatory bodies, and service suppliers, while maintaining flexibility of these interactions and the ability for new market participants to enter easily. Autonomy is an indispensable part of the proposed architecture in enabling efficient data sharing, coordination between STM participants and safe flight operations. Examples of autonomy within STM include syncing multiple non-authoritative catalogs of resident space objects, or determining which spacecraft maneuvers when preventing impending conjunctions between multiple spacecraft. The STM prototype is based on modern micro-service architecture adhering to OpenAPI standards and deployed in industry standard Docker containers, facilitating easy communication between different participants or services. The system architecture is designed to facilitate adding and replacing services with minimal disruption. We have implemented some example participant services (e.g. a space situational awareness provider/SSA, a conjunction assessment supplier/CAS, an automated maneuver advisor/AMA) within the prototype. Different services, with creative algorithms folded into then, can fulfil similar functional roles within the STM architecture by flexibly connecting to it using pre-defined APIs and data models, thereby lowering the barrier to entry of new players in the STM marketplace. We demonstrate the STM prototype on a multiple conjunction scenario with multiple maneuverable spacecraft, where an example CAS and AMA can recommend optimal maneuvers to the spacecraft operators, based on a predefined reward function. Such tools can intelligently search the space of potential collision avoidance maneuvers with varying parameters like lead time and propellant usage, optimize a customized reward function, and be implemented as a scheduling service within the STM architecture. The case study shows an example of autonomous maneuver planning is possible using the API-based framework. As satellite populations and predicted conjunctions increase, an STM architecture can facilitate seamless information exchange related to collision prediction and mitigation among various service applications on different platforms and servers. The availability of such an STM network also opens up new research topics on satellite maneuver planning, scheduling and negotiation across disjoint entities.

space traffic management↗

Octahedral rotations in Ruddlesden-Popper layered oxides under pressure from first principles

The combination of reduced dimensionality and tunable structural distortions in layered perovskite oxides makes these materials ideal platforms for designing novel properties and functionalities. One example is hybrid improper ferroelectricity in n = 2 Ruddlesden-Popper oxides, where the combination of a layered crystal structure and rotations of the metal-oxide octahedra break symmetry and induce a polarization. Precisely controlling the octahedral rotation distortions, for example by the application of hydrostatic pressure, provides a pathway to tune and optimize the properties of these materials. Here we combine group theoretic methods, density functional theory calculations, and Landau theory analysis to investigate how octahedral rotations respond to pressure in the hybrid improper ferroelectrics Sr 3 Zr 2 O 7 , Ca 3 Ti 2 O 7 , and Sr 3 Sn 2 O 7 . We find that factors that are known to control the pressure response of ABO 3 perovskites—the formal charge of the A- and B-site cations, tolerance factor, and B-site chemistry—also impact the pressure response of these layered perovskites. We also show that coupling between the octahedral rotation and strain order parameters plays a key role in determining the overall pressure response. Despite some similarities, we find that these layered perovskites display a distinct pressure response compared to their ABO 3 perovskite analogs. By identifying trends and underlying mechanisms that control octahedral rotations in Ruddlesden-Popper oxides under pressure, this work lays the foundation for tailoring the structure and properties of these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Monitoring for Additive Manufacturing Technologies: Report on Progress, Achievements, and Limitations of Monitoring Techniques

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to produce multiple nuclear components to be assembled into a fully functional microreactor core. AM was selected as the main manufacturing technology of choice for TCR because it has the potential to disrupt the nuclear industry on two fronts: (1) it enables the manufacturing of very complex geometries with optimized and tailored material properties for the intended use of the component, opening up new options for reactor designs, and (2) it allows for a better understanding of the manufacturing process through real-time in situ monitoring, data analytics, and artificial intelligence that can lead to a streamlined qualification and certification process. Within TCR, the development and deployment of a digital platform aims at addressing the latter opportunity. As part of this effort, the collection of pedigree data sets is vital, should these data be generated before, during, or after the manufacturing process. This report focuses on the collection of manufacturing process data using systems instrumentation and monitoring. It presents an inventory of the various monitoring modalities installed on the manufacturing systems by the machine manufacturer or specifically designed by our team to fill information gaps. It also provides details on other relevant data streams available and leverageable to evaluate the manufacturing process on all classes of AM systems investigated during the first year of this program. Through examples, the report gives an overview of the data collected and presents a path forward for the digital platform.

42 ENGINEERING↗

Advancement of Certification Methods and Applications for Industrial Deployments of Components Derived from Advanced Manufacturing Technologies

One goal of the Advanced Materials and Manufacturing Technologies subprogram, within the Department of Energy’s (DOE) crosscutting technology development program, is to advance the qualification and certification of parts and components created via additive manufacturing (AM). AM offers a new paradigm for the design and optimization of new nuclear components, and for observing and tracking manufacturing performance and potential defects in a way that is not possible with traditional approaches. Tracking and evaluating these in situ data can lead to the estimation of local material properties and, with the use of engineering analysis tools, the estimation of component performance during operation. To achieve these objectives, a digital platform certification approach was developed and is summarized in this report.

36 MATERIALS SCIENCE↗

Viability of Data Analytics to Ascertain Component Performance for Additive Manufacturing

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to produce multiple nuclear components to be assembled into a fully functional microreactor core. AM was selected as the main manufacturing technology for TCR because it has the potential to disrupt the nuclear industry on two fronts: (1) it enables the manufacturing of very complex geometries with optimized and tailored material properties for the intended use of the component, opening up new options for reactor designs, and (2) it allows for a better understanding of the manufacturing process through real-time in situ monitoring, data analytics, and artificial intelligence, which can lead to a streamlined qualification and certification process. Within TCR, the development and deployment of a digital platform aims at addressing the latter opportunity. As part of this effort, the collection of pedigree datasets is vital, should these data be generated before, during or after the manufacturing process. This report focuses on the development of data analytics tools enabling qualitative assessment of the manufacturing processes to automate the identification of flaws in in situ monitoring imagery and to correlate those flaws to the resulting mechanical testing data. Through examples, the report gives an overview of the data collected and presents a path forward for the digital platform.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗

Flight experience with altitude hold and Mach hold autopilots on the YF-12 aircraft at Mach 3

The altitude hold mode of the YF-12A airplane was modified to include a high-pass-filtered pitch rate feedback along with optimized inner loop altitude rate proportional and integral gains. An autothrottle control system was also developed to control either Mach number or KEAS at the high-speed flight conditions. Flight tests indicate that, with the modified system, significant improvements are obtained in both altitude and speed control, and the combination of altitude and autothrottle hold modes provides the most stable aircraft platform thus far demonstrated at Mach 3 conditions.

Gilyard, G. B.↗

Nonlinear Motion Cueing Algorithm: Filtering at Pilot Station and Development of the Nonlinear Optimal Filters for Pitch and Roll

Telban and Cardullo have developed and successfully implemented the non-linear optimal motion cueing algorithm at the Visual Motion Simulator (VMS) at the NASA Langley Research Center in 2005. The latest version of the non-linear algorithm performed filtering of motion cues in all degrees-of-freedom except for pitch and roll. This manuscript describes the development and implementation of the non-linear optimal motion cueing algorithm for the pitch and roll degrees of freedom. Presented results indicate improved cues in the specified channels as compared to the original design. To further advance motion cueing in general, this manuscript describes modifications to the existing algorithm, which allow for filtering at the location of the pilot's head as opposed to the centroid of the motion platform. The rational for such modification to the cueing algorithms is that the location of the pilot's vestibular system must be taken into account as opposed to the off-set of the centroid of the cockpit relative to the center of rotation alone. Results provided in this report suggest improved performance of the motion cueing algorithm.

Zaychik, Kirill B.↗

Rotorcraft Diagnostics

Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer decision support for optimal maintenance.

Haste, Deepak↗