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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Operation at Reduced Atmospheric Pressure and Concept of Reliability Redundancy for Optimized Design of Insulation Systems

Electrified transportation is calling for insulation design criteria that is adequate to provide elevated levels of power density, power dynamics and reliability. Increasing voltage levels are expected to cause accelerated intrinsic and extrinsic aging effects which will not be easily predictable at the design stage due to a lack of suitable modeling. Designing reliable insulation systems would require finding solutions able to control accelerated aging due to an unpredictable increase of intrinsic stresses and the onset of extrinsic stresses as partial discharges. This paper proposes the concept of reliability redundancy for the insulation design of aerospace electrical asset components, which is also validated at lower-than-standard atmospheric pressure. The principle is that extrinsic-aging-free design might be achieved upon determining the aging stress or abnormal service stresses distribution and being sure that aging will not generate conditions that can incept extrinsic aging (partial discharges) during operation life. However, such information is never, in practice, fully available to insulation system designers. Hence, especially in critical applications such as electrified aircraft, aerospace, and combat ships a further level of reliability should be added to a partial-discharge-free design, which can consist of the use of corona-resistant materials and/or of life models able to consider the accelerated aging effect of partial discharges (or any other type of extrinsic-accelerated aging factor). Innovative life modeling considering both extrinsic and intrinsic aging stresses, insulating material testing to estimate model parameters, and a metric for quantifying the extent of corona (or partial discharge) resistance can lead to establishing feasibility and limit conditions for optimized or fully reliability-redundant design. It is shown in the paper that if an extrinsic-aging-free design is not feasible, and it is therefore replaced by a redundant design, a further level of reliability redundancy can be provided by effective condition monitoring plans.

Montanari, Gian Carlo↗
DOE OSTI2020

Will Solar Panels Help When the Power Goes Out? Planning for PV Resilience

PV systems, like all energy systems, must chart a difficult course in order to improve resilience. They need to simultaneously withstand extreme conditions that cause grid power disruptions, be configured in a way that allows electricity to be delivered to meet the PV user's needs, and overcome disruptions arising from solar resource intermittency. Certain considerations reveal themselves as key to a PV system's resilience benefits. Choice of hardware is critical, as is site selection for the PV array. Voluminous evidence in a hurricane context demonstrates that durable hardware, properly maintained and sited, leads to PV systems surviving extreme weather with their functionality intact. Structurally weak or poorly maintained PV equipment, on the other hand, has demonstrated failures during extreme weather events. PV system stakeholders should ensure that best practices are followed for hardware procurement and siting. It is also important to understand that PV systems are not one-size-fits-all. While incorporating islanding capabilities and energy storage into the system's electrical topology will typically enhance resilience, the user's needs will determine the optimally resilient conformation of any given system. These factors - appropriate hardware, siting, maintenance, and system design - are the primary drivers of PV resilience. PV systems possess high potential for resilient energy generation due to their distributed, abundant, and free fuel supply, but the technology itself does not inherently lead to resilient outcomes. Realizing PV's potential for resilience requires consideration of these determinative factors.

14 SOLAR ENERGY↗
DOE OSTI2025

Powernet in Farms Project

Coordinating behind-the-meter (BTM) distributed energy resources (DERs) is critical to ensuring efficiency and reliability for consumers facing an increasingly variable grid supply. Outside of very controlled environments, however, such coordination of heterogeneous resources at scale has remained a challenge due to harsh field conditions, the lack of adequate communication infrastructure, and the difficulty of modeling the system. The intent of this research was to refine the Powernet system deployed in a California dairy farm to achieve the following objectives: a) validate the results of the previous deployment and b) validate new hypothesis about system performance based on the simulation of the new system. The new system design would reduce the overall system cost, and achieve a payback period of less than 3 years, demonstrating the feasibility of such system and its relevance for a segment not well known for technology advancements in power systems. The new proposed system was significantly cheaper than the original design, which would enable the solution to be cost effective and likely economically viable. However, due to significant delays in project start date which affected funding availability, overlap with prior scheduled mandatory military leave from key members of the project team, and customer drop-out, due to the significant delays, which could not be replaced in time, caused the project to be ended prior to completion.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Ground Source Heat Pump Screening Tool and Related Resources

This archive contains both a link to Oak Ridge National Laboratory's Ground Source Heat Pump (GSHP) Screening Tool and related resources documenting its development, technical features, and applications. The web-based screening tool is a techno-economic analysis resource designed to evaluate the feasibility, costs, and benefits of implementing GSHP systems in buildings across various U.S. climate zones. It is intended for use by building owners, HVAC system designers, and installers to support decision-making in residential and commercial applications, incorporating advanced modeling capabilities such as ground heat exchanger design. The included resources detail the tool's creation and use, covering topics such as innovative ground heat exchanger design methodologies, the development of an open library of g-functions for borehole configurations, and studies on GSHP performance and economic viability in retrofitting single-family homes.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Organic Rankine Cycle Integration and Optimization for High Efficiency CHP Genset Systems (Final Technical Report)

This project successfully advanced the integration of Organic Rankine Cycle (ORC) technology with reciprocating engine–based combined heat and power (CHP) systems to improve electrical efficiency, total CHP efficiency, and grid-responsive operation. Over three budget periods, the work progressed from high-temperature ORC component development and thermodynamic model validation to next-generation system design, working fluid transition, and techno-economic analysis. Key technical accomplishments include development and validation of a thermodynamic model capable of accurately predicting ORC performance across an expanded temperature and pressure envelope; successful identification and validation of low-global-warming-potential (GWP) working fluids—most notably R1233zd(E)—as viable replacements for R245fa; and demonstration of scalable ORC architectures suitable for integration with 1–20 MW class reciprocating engines. These advances enable flexible CHP configurations that can increase electrical output while maintaining high overall utilization of available thermal energy. The project also produced a clean-sheet design for a next-generation ORC system targeting substantially higher power output per unit, supported by detailed component selection, heat exchanger evaluation, and system-level modeling. Techno-economic analyses indicate that ORC-enabled flexible CHP systems can meet or exceed Department of Energy (DOE) efficiency targets while providing value to both facility operators and the electric grid.. Late-stage testing of the largest next-generation ORC prototype identified limitations related to pump net positive suction head (NPSH) requirements and condenser flooding under certain operating conditions. Although these issues constrained full validation of that configuration within the project timeframe, they provided clear and actionable design guidance for future system refinements. Importantly, validated modeling, smaller-scale testing, and working fluid evaluations confirmed the technical viability of the overall approach. In aggregate, this project met its core objectives by establishing validated design tools, de-risking key ORC technologies for CHP applications, and defining a credible pathway toward commercialization of flexible, high-efficiency CHP systems. The results form a strong foundation for continued development and deployment beyond the conclusion of the DOE-funded effort.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Network Uncertainty Quantification for Analysis of Multi-Component Systems

To impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages of the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.

42 ENGINEERING↗
DOE OSTI2023

Improving Experimental Design through Uncertainty Analysis

In this paper, the development of a fission-gas collecting and physical-analysis-enabling instrument was proposed for small-volume determination. Analysis specifications require a design capable of accurately and repeatably determining volumes in the range of 0.07–2.5 mL. This system relies on a series of gas expansions originating from a cylinder with known internal volume. The combined gas law is used to derive the unknown volumes from these expansions. Initial system designs included one of two known volumes, 11.85 ± 0.34 mL and 5.807 ± 0.078 mL, with a manifold volume of 32 mL. Results obtained from modeling this system’s operation showed that 0.07 mL can be determined with a relative expanded uncertainty greater than 300% (k = 2) for a single replicate, which was unacceptable for the proposed experimental design. Initial modeling showed that the volume connecting the known volume and rodlet, i.e., the manifold volume, and the sensitivity of the pressure sensor were key contributors to the expanded uncertainty of the measured rodlet volume. The system’s design limited the available options for pressure sensors, so emphasis was placed on the design of the manifold volume. The final system design reduced the manifold volume to 17 mL. These changes in design, combined with replicate analysis, were able to reduce the relative expanded uncertainty by ±12% (k = 2) for the 0.07 mL volume.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Filtration Performance Results: Sierra Peaks Material No. 4

Sandia National Laboratories (SNL) assessed the filtration performance of materials from Sierra Peaks to identify alternatives which may perform similarly to materials used in FDA-approved N95 respirators. This work is meant to characterize the aerosol performance of materials to give Sierra Peaks information for them to determine if they elect to submit masks made using these materials for follow-on N95 certification testing at an accredited facility. The R&D testbed used is a large-scale filtration system designed to test commercial filter boxes. System modifications were performed to simulate, where possible, parameters defined by the National Institute for Occupational Safety and Health (NIOSH) for certification of filter materials for N95 respirators (NIOSH 2019). The system is a pull-through design. Air enters through a Laminar Flow Element (LFE) and the volumetric flow is measured based on the pressure drop across the LFE. Pressure is measured via a Pressure Transducer (PT). The air then passes through a High Efficiency Particulate Air (HEPA) filter to purge the air of ambient airborne particulates. Test aerosol is injected into the flow shortly after and mixing is induced via a coarse mesh. The airflow is allowed to fully develop prior to arriving at the test section. The aerosol then passes through the test material mounted in a box in the test section. Pressure drop across the test article is measured and aerosol sampling probes measure the aerosol concentrations upstream and downstream of the sample. The air passes through a second HEPA filter prior to being exhausted to ambient by a blower. A Topas aerosol generator is used to produce the test aerosol from Sodium Chloride (NaC1) dissolved in deionized (DI) water. Generated aerosol passes through a heated mixing chamber and a desiccant dryer to produce nanosized solid-state particulates. A dilution loop allows for the aerosol concentration to be regulated. The aerosol sampling probes upstream and downstream of the test section are aligned with the flow path. These are ducted directly to the aerosol sizing and counting instruments. A Laser Aerosol Spectrometer (LAS) was used for data collection in the original configuration of the system and was also used for initial testing in this project. Because the lower measurement range for the LAS is 90 nanometers (nm), the LAS was switched out for a more complicated Scanning Mobility Particle Sizer (SMPS) spectrometer system. The SMPS is comprised of an Electrostatic Classifier (EC), Differential Mobility Analyzer (DMA), and a Condensation Particle Counter (CPC). This enabled data collection at 75 nm, the particle size called out in the NIOSH guidelines.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Robust Parameter Design on Dual Stochastic Response Models With Constrained Bayesian Optimization

In engineering system design, minimizing the variations of the quality measurements while guaranteeing their overall quality up to certain levels, namely the robust parameter design (RPD), is crucial. Recent works have dealt with the design of a system whose response-control variables relationship is a deterministic function with a complex shape and function evaluation is expensive. In this work, we propose a Bayesian optimization method for the RPD of stochastic functions. Dual stochastic response models are carefully designed for stochastic functions. The heterogeneous variance of the sample mean is addressed by the predictive mean of the log variance surrogate model in a two-step approach. We establish an acquisition function that favors exploration across the feasible and optimality-improvable regions to effectively and efficiently solve the stochastic constrained optimization problem. Further, the performance of our proposed method is demonstrated by the extensive numerical and case studies. Note to Practitioners-Many manufacturing processes involve undesirable variations, which create variations in the final products. For example, many emerging manufacturing processes, such as nanomanufacturing, involve complex physical and chemical dynamics and transformation, creating variations in the manufacturing output. In such processes, it is crucial to design the manufacturing processes or products so that they have minimum variations in their quality. Meanwhile, it is also important to maintain the overall quality of the designed processes or products. Furthermore, acquiring data from many advanced manufacturing processes is often very costly, especially in the designing stage. In this work, we propose a data-driven method that automatically finds the best setting of manufacturing processes or products with the minimum variations of quality and a given constraint on the average quality satisfied. Our proposed method is used before conducting every experiment; It analyzes the historical data from previous experiments and provides a setting to be used in the next experiment. Our proposed method efficiently utilizes the historical data, and thus finds the best robust setting by conducting only a small number of experiments.

42 ENGINEERING↗
DOE OSTI2024

Engineering in Cyber Resilience with Cyber-Informed Engineering

Engineers have super powers to provide cybersecurity resilience with deterministic engineering solutions and to protect systems from the most catastrophic consequences that a cyber saboteur could cause. Come to this session to learn how to use engineering risk management skills to harden your engineered systems from cyberattacks. Objective 1 Identify what system functions could be digitally induced to cause undesired high-impact consequences. Objective 2 Analyze how loss or instability of digital controls in a subsystem could lead to high-impact consequences. Objective 3 Analyze how loss or instability in the digital connectivity between systems could lead to high-impact consequences. Objective 4 Identify engineering controls which could build resilience by eliminating digital loss or instability pathways or reduce the impact of digital loss or instability. This presentation will introduce Cyber-Informed Engineering, described below, and walk participants through specific engineering use cases to show how engineers can consider the potential for cyber sabotage in their existing system designs and enact deterministic engineering-based controls which eliminate pathways for attack or mitigate specific consequences. A wide variety of application use cases will be considered so that audience members can align the material with familiar engineering applications. CIE is an engineering approach that integrates cyber resilience into the conception, design, build, and operation of any physical system that has digital connectivity, sensors, monitoring, or control. CIE offers the opportunity to use engineering to eliminate or mitigate avenues for cyber attack—starting from the earliest stage of design and continuing throughout the system’s lifecycle. Today, engineers and industrial control system (ICS) technicians build engineered systems with specific goals for safety, reliability, and functionality. While systems engineering includes considerable safety and failure mode analysis, cybersecurity risks are often not specifically addressed—particularly the risks of intentional cyber compromise, exploitation, and misuse. Cyber-Informed Engineering pairs well with traditional cyber defenses and offers an extra designed-in protection to eliminate the most catastrophic consequences which can be realized by an adversary should traditional cyber defenses fail.

42 ENGINEERING↗
DOE OSTI2021

Designing the Insulation System for Motors in Electrified Aircraft: Optimization, Partial Discharge Issues and Use of Advanced Materials

Designing the insulation system for motors to be used in electrical aircraft requires efforts for maximizing specific power, but, in parallel, particular attention to achieve high reliability. As a major harm for organic insulation systems is partial discharges, design must be able to infer their likelihood during any operation stage and handle their potential inception. This paper proposes a new approach to carry out optimized or conservative insulation system designs which can provide the specified life at the chosen failure probability as well as look at the option of possibly reducing the risk of partial discharges to zero, at any altitude. Examples of designing turn, phase to ground and phase-to-phase insulation systems are reported, with cases where the design can be optimized and other cases where the optimized design does not pass IEC testing standard. Therefore, the limits for design feasibility as a function of the required level of safety and reliability are discussed, showing that the presence of partial discharges cannot be always avoided even through conservative design criteria. Therefore, the use of advanced, corona-resistant materials must be considered, in order to reach a higher, sometimes redundant, level of reliability.

Ramin, Robin (ORCID:0000000211455006)↗
DOE OSTI2022

Preliminary Reversible Solid Oxide System Specification

This report presents the preliminary documentation of a 10 MWe DC reversible solid oxide cell (rSOC) system designed to use both electrical and thermal energy from a nuclear power plant (NPP). The system is designed to consume 10 MWe DC in electrolysis mode while producing hydrogen from demineralized feedwater. In fuel cell mode, the same stacks produce 2.37 MWe DC of electricity by reacting hydrogen and oxygen, while generating water as a byproduct which is recycled to be used later in the electrolysis mode. The system detailed in this specification is a high-temperature steam electrolysis (HTSE) system when operated in the electrolysis mode. HTSE systems have the benefit of producing hydrogen at a higher efficiency than conventional low-temperature electrolysis (LTE) systems. In this report it is assumed that some of the heat required for HTSE operation comes from an NPP. Heat extraction from an NPP for use in electrolysis mode of the rSOC system allows preheating and vaporization of feedwater before recuperators and trim heaters raise the feed temperature to the approximately 800 °C before entering the solid oxide stacks. The purpose of an rSOC system in a utility company setting is to employ energy arbitrage with a dispatchable demand load which can consume excess electricity generation during times of low grid demand / high generation and can produce electricity for the grid during times of high grid demand / low generation. There is a wide range of energy storage technologies that could be used for utility-scale energy arbitrage (utility-scale battery storage is considered the baseline technology), the object of this work is not to compare and contrast rSOC technology with any of these other technologies, but only to present this preliminary design for consideration and for use in future conceptual or front end engineering design (FEED) work. This document is not meant to be a final specification or definitive description of the rSOC system, but it is meant to showcase preliminary process modeling results, provide boundary conditions and interface requirements such as input feed and utility stream flowrates, temperatures, and pressures as well as thermal and electrical energy requirements, and output conditions in both electrolysis mode and fuel cell mode. These results are intended to inform the future development of a conceptual demonstration-scale study to assess the technical and economic feasibility of a future demonstration of an rSOC integrated project at an NPP.

08 HYDROGEN↗
DOE OSTI2023

Extreme-scale stochastic optimization and simulation via learning-enhanced decomposition and parallelization (Final Technical Report)

Stochastic optimization and simulation models ubiquitously arise in designing and operating complex service/engineering systems. They can be extreme in scale due to high-dimensional data and decisions, and can also involve decisions made sequentially in response to newly revealed data, both causing significant computational challenge. The objective of this research is to explore a unified framework that integrates machine learning with discrete optimization and risk-averse modeling, to improve the efficiency of decomposition paradigms for stochastic optimization and simulations at extreme scale. The models we consider represent a broad class of complex decision-making problems, where 0-1 or continuous decisions are made before and/or after knowing multiple sources of uncertainties that could be correlated. We will employ machine learning methods to dynamically decide and prioritize computational procedures, including cut generation, branching, and bounding of the optimal objective. Furthermore, the research will shed new lights on the traditional decomposition algorithms for extreme-scale computing. Deliverables of the research include new modeling and computational methods for advancing the state-of-the-art research in optimization and simulation, bringing many relevant risk-averse, data-driven optimization problems in practice within the range of tractability. Examples include distributed computing server scheduling and sensor deployment for monitoring critical infrastructures. Success in this effort will enable progress in solving multiple extreme-scale problems in the complex system design and operations arising from DoE missions in energy, environment, and national security.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Cryogenic Performance of the SPT-SLIM Receiver

The South Pole Telescope Shirokoff Line Intensity Mapper (SPT-SLIM) is a millimeter-wave line-intensity mapping experiment, deployed on the South Pole Telescope (SPT) during the 2024-2025 Austral Summer season. This pathfinder experiment serves to demonstrate the on-sky operation of multi-pixel on-chip spectrometer technology. We present on the cryogenic performance of the SPT-SLIM receiver for this Year 1 observing campaign. The SPT-SLIM receiver utilizes an Adiabatic Demagnetization Referigerator (ADR) for cooling the focal plane of superconducting filterbank spectrometers to a temperature of 150mK. We demonstrate stable thermal performance of the focal plane module during observing operations in line with thermal modelling, enabling a cryogenic operation efficiency above 80%. We also report on the receiver control system design utilizing the Observatory Control System (OCS) platform for automated cryogenic operation on the SPT.

Young, Matthew [Fermilab]↗
DOE OSTI2023

Hybrid Solar System (Final Scientific/Technical Report)

GTI Energy (GTI) teamed with the University of California at Merced (UCM) to scaleup the hybrid solar system (HSS) technology for demonstrating its performance at the US Gypsum (USG) plant in Plaster City, California. The technology integrates two-stage concentrating solar collector with matching particle thermal transport and storage (TSS) system to deliver cost-effective, and on-demand distributed high temperature industrial process heat up to 600°C with solar thermal, in this case to a gypsum kettle, to reduce its fuel use and carbon footprint. Current solar technologies, which reach these temperatures, are not distributable (towers) or cost-effective (dish). The research team developed a conceptual system design for host site retrofit, including preliminary heat balance, process flow diagram, particle to process heat exchanger and equipment placements at the site. Subsequently, parallel efforts were carried out at UCM to design, build and test a 12 m long commercial scale prototype concentrating thermal-only collector system and at GTI to design, build and test a matching 650°C capable particle TTS system. The nominal 50 kWth collector consists of a parabolic trough and three 4 m long two-stage receivers in series. Prior to on-sun testing, a 4 m long receiver was fabricated and successfully tested at 650 °C in a laboratory setting for 100 hrs of continuous operation showing less than 15% radiation loss. A 7 m wide x 17 m long parabolic trough was then installed at UCM for on-sun testing of the 12 m long receiver, and concurrently several 4 m long receivers were built. The optics of the parabolic trough were calibrated, and on-sun test were carried out on 12 m long receivers. During tests, the intense solar radiation (53x) caused the absorber tubes in the receivers to bend, reducing the overall optical efficiency. To address the bending issue, a self-consistent algorithm that includes ray tracing, thermal and deformation models was developed to perform thermal stress analysis on absorbers for parabolic solar collectors. Results obtained with this algorithm showed a dramatic rise in deformation as absorber tube length increases. A combined efficiency parameter that includes the occluded area for the mounts was developed to obtain an optimized tube length obtained. Based on the results, a length of 2.7 m for the absorber + 0.2 m for the coupler was chosen to minimize any bending and optimize optical efficiency while maintaining ease of mounting. The associated particle TTS system was designed, built and successfully tested at GTI. It includes storage, receiving and lock hoppers and piping that simulates the transfer of captured solar energy to an actual industrial furnace. Tests over 77 charge-discharge cycles demonstrated <2% particle degradation, with no problematic particle accumulations and no flow interruptions. The piping pressure drop was about 5 psi. The team also worked with Stanley Consultants (Stanley) to prepare conceptual and preliminary engineering packages to facilitate follow-on development and commercialization efforts. These include process and instrumentation diagram’s (P&ID’s), general arrangements, electrical one-line, project definitions document, equipment data sheets, schedule, and construction cost estimate for 2 MWth system. Updated HSS technology commercialization and customer engagement plans and detailed costs and evaluated market trade-offs and manufacturing.

03 NATURAL GAS↗
DOE OSTI2023

Moving-horizon false data injection attack design against cyber–physical systems

Systematic attack design is essential to understanding the vulnerabilities of cyber–physical systems (CPSs), to better design for resiliency. In particular, false data injection attacks (FDIAs) are well-known and have been shown to be capable of bypassing bad data detection (BDD) while causing targeted biases in resulting state estimates. However, their effectiveness against moving horizon estimators (MHE) is not well understood. In fact, this paper shows that conventional FDIAs are generally ineffective against MHE. One of the main reasons is that the moving window renders the static FDIA recursively infeasible. Here, this paper proposes a new attack methodology, moving-horizon FDIA (MH-FDIA), by considering both the performance of historical attacks and the current system’s status. Theoretical guarantees for successful attack generation and recursive feasibility are given. Numerical simulations on the IEEE-14 bus system further validate the theoretical claims and show that the proposed MH-FDIA outperforms state-of-the-art counterparts in both stealthiness and effectiveness. In addition, an experiment on a path-tracking control system of an autonomous vehicle shows the feasibility of the MH-FDIA in real-world nonlinear systems.

42 ENGINEERING↗