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At least 1,189 records · Page 66

Pt-Ligand single-atom catalysts: tuning activity by oxide support defect density

The support–metal interaction is an important element of heterogeneous catalyst design and is particularly critical for the rapidly growing field of single-atom catalysts (SACs). In this work, we investigate the impact of varying the defect density of the titania support on metal–organic Pt SACs for hydrosilylation reactions. Pt SACs are decorated on the powder titania support, employing a metal–ligand interaction with a dipyridyl-tetrazine ligand (DPTZ). The single-atom nature of Pt is verified by X-ray absorption spectroscopy (XAS) on both pristine and defective titania surfaces. These Pt species have a +2 oxidation state and are stabilized by bonding with DPTZ, surface oxygen, and residual chloride from the metal precursor. The catalytic activity is evaluated for the alkene hydrosilylation reaction and it is discovered that the activity of Pt-ligand is positively correlated with the defect density of the titania support. The turn-over number (TON) is calculated to be 12 530 for Pt SACs on a defective surface, which is significantly higher than Pt SACs on a pristine titania surface (830) for the same reaction period (10 min) under the same conditions (70 °C). We ascribe the high activity of Pt SACs on defective titania surfaces to two aspects: the coordination of Pt with more chloride than on pristine titania surfaces, which shortens the induction period of the reaction, and the preferential dispersion of Pt–DPTZ units on defective regions of titania surfaces, allowing facile contact between Pt sites and reactants. The supported Pt–DPTZ SACs show high stability through multiple cycles of batch reactions. This work demonstrates an efficient approach to improve the activity and stability of SACs by optimizing the metal–support interaction, which can also be applied to other oxide surfaces to further develop next-generation heterogeneous single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services

With increasing penetrations of wind generation on electric grids, wind power plants (WPPs) are encouraged to provide frequency ancillary services (FAS); however, it is a challenge to ensure that variable wind generation can reliably provide these ancillary services. This paper proposes using a battery energy storage system (BESS) to ensure the WPPs' commitment to FAS. This method also focuses on reducing the BESS's size and extending its lifetime. In this paper, a state-machine-based coordinated control strategy is developed to utilize a BESS to support the obliged FAS of a WPP (including both primary and secondary frequency control). This method takes into account the operational constraints of the WPP (e.g., real-time reserve) and the BESS (e.g., state of charge [SOC], charge and discharge rate) to provide reliable FAS. Meanwhile, an adaptive SOC-feedback control is designed to maintain SOC at the optimal value as much as possible and thus reduce the size and extend the lifetime of the BESS. In conclusion, the effectiveness of the control strategy is validated with an innovative, multi-area, interconnected power system simulation platform that can mimic realistic power systems operation and control by simulating real-time economic dispatch, regulating reserve scheduling, multi-area automatic generation control, and generators' dynamic response.

25 ENERGY STORAGE↗

Agent-Based Coordination Scheme for PV Integration (ABC4PV)

Renewables and especially photovoltaics (PV) have benefitted significantly from a host of incentives and policies targeted toward enhanced integration and adoption of specific energy technologies. However, with the push to move forward into a subsidy-free market framework, behind-the-meter residential PV applications have generally struggled to retain their value (unlike utility scale and commercial projects) [1]. This project focused on developing control-theoretic solutions aimed at improving the integration and interaction of behind-the-meter residential PV with other distribution system assets (controllable and non-controllable) to enhance the integrated value of residential PV. To this end, a suite of decentralized control methodologies have been developed to enable effective coordination and control of behind-the-meter residential load customers’ PV, battery storage systems (BSS), controllable loads and other similar assets within a distribution feeder. This interaction aims at procuring energy savings and, thus, energy bill savings. The main source of savings is drawn from reducing the effect of demand charge pricing and is realized at the feeder level, assuming community level interaction and management among the aforementioned assets. Optimal control of the assets is implemented with a distributed optimization methodology, leveraging consensus-based algorithms. The results gathered from the optimal control simulations demonstrates that the savings can be duly achieved and the algorithm decision times (to dynamically control asset set points, for example) are fast. As for the overall efficiency of PV+BSS systems, to procure energy savings from curtailment of the demand charge pricing effects, the optimal control is set up so as to minimize the variance of the load for all customers, throughout a feeder and throughout time in a rolling horizon scheduling with model predictive control. The control takes into account inter-temporal electrochemical storage (battery) degradation costs: specifically, we have developed a long-term lifetime model for the BSS that weighs in the effect of the degradation factor in the dispatch formulations, thus, a considerable operating cost that affects energy decision making. The levelized cost of energy (LCOE – redefined for the purpose of quantifying asset integration effectiveness through the customers’ energy cost) is shown to be below the threshold set for the combined PV+BSS topology of $ 0.14/kWh for multiple cases of PV penetration all the way up to 50%, provided that a policy of shared ownership of and savings is in place. Further, the LCOE calculated for the case before the deployment PV+BSS systems is also achievable, i.e. the deployment of PV+BSS, if planned and scheduled optimally. will have no effect on customers’ energy costs. From the control methodology viewpoint, the developed consensus-based algorithms are shown to converge for a wide range of problem cases (spanning normal operating scenarios and contingencies), guaranteeing dispatch solutions under forecasting errors, communication break-downs and cyber-security attacks. The proposed control solutions are scalable and real-time implementable, with dispatch computations and device set-point updates converging in less than 2s in most practical instances of the above events.

14 SOLAR ENERGY↗

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves the OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve an improvement of more than tenfold in the speed of convergence compared to the centrally coordinated primal-dual algorithm.

Zhou, Xinyang↗

Method and apparatus for configuration control of redundant robots

A method and apparatus to control a robot or manipulator configuration over the entire motion based on augmentation of the manipulator forward kinematics is disclosed. A set of kinematic functions is defined in Cartesian or joint space to reflect the desirable configuration that will be achieved in addition to the specified end-effector motion. The user-defined kinematic functions and the end-effector Cartesian coordinates are combined to form a set of task-related configuration variables as generalized coordinates for the manipulator. A task-based adaptive scheme is then utilized to directly control the configuration variables so as to achieve tracking of some desired reference trajectories throughout the robot motion. This accomplishes the basic task of desired end-effector motion, while utilizing the redundancy to achieve any additional task through the desired time variation of the kinematic functions. The present invention can also be used for optimization of any kinematic objective function, or for satisfaction of a set of kinematic inequality constraints, as in an obstacle avoidance problem. In contrast to pseudoinverse-based methods, the configuration control scheme ensures cyclic motion of the manipulator, which is an essential requirement for repetitive operations. The control law is simple and computationally very fast, and does not require either the complex manipulator dynamic model or the complicated inverse kinematic transformation. The configuration control scheme can alternatively be implemented in joint space.

Seraji, Homayoun↗

Towards a generalized computational fluid dynamics technique for all Mach numbers

Currently there exists no single unified approach for efficiently and accurately solving computational fluid dynamics (CFD) problems across the Mach number regime, from truly low speed incompressible flows to hypersonic speeds. There are several CFD codes that have evolved into sophisticated prediction tools with a wide variety of features including multiblock capabilities, generalized chemistry and thermodynamics models among other features. However, as these codes evolve, the demand placed on the end user also increases simply because of the myriad of features that are incorporated into these codes. In order for a user to be able to solve a wide range of problems, several codes may be needed requiring the user to be familiar with the intricacies of each code and their rather complicated input files. Moreover, the cost of training users and maintaining several codes becomes prohibitive. The objective of the current work is to extend the compressible, characteristic-based, thermochemical nonequilibrium Navier-Stokes code GASP to very low speed flows and simultaneously improve convergence at all speeds. Before this work began, the practical speed range of GASP was Mach numbers on the order of 0.1 and higher. In addition, a number of new techniques have been developed for more accurate physical and numerical modeling. The primary focus has been on the development of optimal preconditioning techniques for the Euler and the Navier-Stokes equations with general finite-rate chemistry models and both equilibrium and nonequilibrium thermodynamics models. We began with the work of Van Leer, Lee, and Roe for inviscid, one-dimensional perfect gases and extended their approach to include three-dimensional reacting flows. The basic steps required to accomplish this task were a transformation to stream-aligned coordinates, the formulation of the preconditioning matrix, incorporation into both explicit and implicit temporal integration schemes, and modification of the numerical flux formulae. In addition, we improved the convergence rate of the implicit time integration schemes in GASP through the use of inner iteration strategies and the use of the GMRES (General Minimized Resisual) which belongs to the class of algorithms referred to as Krylov subspace iteration. Finally, we significantly improved the practical utility of GASP through the addition of mesh sequencing, a technique in which computations begin on a coarse grid and get interpolated onto successively finer grids. The fluid dynamic problems of interest to the propulsion community involve complex flow physics spanning different velocity regimes and possibly involving chemical reactions. This class of problems results in widely disparate time scales causing numerical stiffness. Even in the absence of chemical reactions, eigenvalue stiffness manifests itself at transonic and very low speed flows which can be quantified by the large condition number of the system and evidenced by slow convergence rates. This results in the need for thorough numerical analysis and subsequent implementation of sophisticated numerical techniques for these difficult yet practical problems. As a result of this work, we have been able to extend the range of applicability of compressible codes to very low speed inviscid flows (M = .001) and reacting flows.

Walters, R. W.↗

Numerical Modeling and Testing of an Inductively-Driven and High-Energy Pulsed Plasma Thrusters

Pulsed Plasma Thrusters (PPTs) are advanced electric space propulsion devices that are characterized by simplicity and robustness. They suffer, however, from low thrust efficiencies. This summer, two approaches to improve the thrust efficiency of PPTs will be investigated through both numerical modeling and experimental testing. The first approach, an inductively-driven PPT, uses a double-ignition circuit to fire two PPTs in succession. This effectively changes the PPTs configuration from an LRC circuit to an LR circuit. The LR circuit is expected to provide better impedance matching and improving the efficiency of the energy transfer to the plasma. An added benefit of the LR circuit is an exponential decay of the current, whereas a traditional PPT s under damped LRC circuit experiences the characteristic "ringing" of its current. The exponential decay may provide improved lifetime and sustained electromagnetic acceleration. The second approach, a high-energy PPT, is a traditional PPT with a variable size capacitor bank. This PPT will be simulated and tested at energy levels between 100 and 450 joules in order to investigate the relationship between efficiency and energy level. Arbitrary Coordinate Hydromagnetic (MACH2) code is used. The MACH2 code, designed by the Center for Plasma Theory and Computation at the Air Force Research Laboratory, has been used to gain insight into a variety of plasma problems, including electric plasma thrusters. The goals for this summer include numerical predictions of performance for both the inductively-driven PPT and high-energy PFT, experimental validation of the numerical models, and numerical optimization of the designs. These goals will be met through numerical and experimental investigation of the PPTs current waveforms, mass loss (or ablation), and impulse bit characteristics.

Parma, Brian↗

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids: Preprint

We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve more than 10-fold improvement in the speed of convergence compared to the centrally coordinated primal-dual algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves the OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve an improvement of more than tenfold in the speed of convergence compared to the centrally coordinated primal-dual algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗

On the utility of finite element theory for computational fluid dynamics

An implicit finite element numerical solution algorithm is derived for the compressible Navier-Stokes equations expressed in generalized coordinates. The theoretical basis utilizes a Galerkin-Weighted Residuals formulation, and extremization of approximation error within the context of a multipole expansion. A von Neumann analysis for a simplified form indicates the algorithm fourth- to sixth-order phase accurate, with third-order dissipation for the elementary linear element construction. Performance is improved for the algorithm constructed using quadratic interpolation. Numerical experiments for shocked duct flows are employed to optimize the several algorithm parameters. Additional numerical solutions validate algorithm accuracy and utility for aerodynamics applications.

Baker, A. J.↗

NASA's Soil Moisture Active and Passive (SMAP) Mission

The Soil Moisture Active-Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Decadal Survey. SMAP will make global measurements of soil moisture at the Earth's land surface and its freeze-thaw state. These measurements will allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing over the boreal latitudes will also reduce a major uncertainty in quantifying the global carbon balance and help to resolve an apparent missing carbon sink over land. The SMAP mission concept will utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna flying in a 680 km polar orbit with an 8-day exact ground track repeat aboard a 3-axis stabilized spacecraft to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these surface observations with advanced modeling and data assimilation to provide estimates of deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP recently completed its Phase A Mission Concept Study Phase for NASA and transitioned into Phase B (Formulation and Detailed Design). A number of significant accomplishments occurred during this initial phase of mission development. The SMAP project held several open meetings to solicit community feedback on possible science algorithms, prepared preliminary draft Algorithm Theoretical Basis Documents (ATBDs) for each mission science product, and established a prototype algorithm testbed to enable testing and evaluation of the performance of candidate algorithms. SMAP conducted an Applications Workshop in September 2009 to coordinate with potential application users interested in the mission data. A draft Applications Plan describing the Project s planned outreach to potential applications users has been prepared and will be updated during Phase B. SMAP made a significant evaluation of the potential terrestrial radio frequency interference (RFI) source environment and established radiometer and radar flight hardware and ground processing mitigation approaches. SMAP finalized its science orbit and orbit injection approach to optimize launch mass and prepared launch and commissioning scenarios and timeline. A science data communications approach was developed to maximize available science data volume to improve science margins while maintaining moderately short data product latencies to support many potential applications using existing ground assets and with minimum impact to the flight system. SMAP developed rigid multi-body and flexible body dynamics and control models and system designs for the 6-meter rotating instrument reflector-boom assembly (RBA) and flight system to confirm pointing and control performance, and devised strategies to efficiently implement on-orbit balancing if needed. Industry partners were selected for the spin mechanism assembly (SMA) and RBA. Preliminary designs for the radar and radiometer were initiated, including constructing breadboards of key assemblies.

Kellogg, Kent↗

Weathering the Storm: Unmanned Aircraft Systems in the Maritime, Atmospheric and Polar Environments

Unmanned systems have the potential to efficiently, effectively, economically, and safely bridge critical observation requirements in an environmentally friendly manner. As the United States Atmospheric, Marine and Arctic areas of interest expand and include hard-to-reach regions of the Earth (such as the Arctic and remote oceanic areas) optimizing unmanned capabilities will be needed to advance the United States science, technology and security efforts. Through increased multi-mission and multi-agency operations using improved inter-operable and autonomous unmanned systems, the research and operations communities will better collect environmental intelligence and better protect our country against hazardous weather, environmental, marine and polar hazards. This presentation will examine UAS (Unmanned Aircraft Systems) operations which includes developing a coordinated effort to maximize the efficiency and capabilities of unmanned systems across the federal government and research partners. Numerous intra- and inter-agency operational demonstrations and assessments have been made to verify and validated these UAS observations. The NASA-specific elements will consist of an overview of NASA UAVs (Unmanned Aerial Vehicles) available to science and recent missions.

Atmospheric↗

Machine Learning Models for Binary Molecular Classification using VUV Absorption Spectra

Machine learning methods were combined with differential absorption spectroscopy measurements in the vacuum-ultraviolet region (5.167 – 9.920 eV) in order to develop predictive capabilities for inferring molecular structure from the spectra. Several types of species were analyzed and, for modeling purposes, were defined using a single classification: (1) alkane, (2) conjugation with oxygen (e.g. diacetyl, ethyl vinyl ether), (3) non-conjugated alkene (e.g. 1-butene, 1,4-cyclohexadiene), (4) oxygen-containing (e.g. 1-butanol, tetrahydrofuran), or (5) cyclic (e.g. cyclopentane, cyclohexanone). The latter molecular classification excluded cyclic ethers. Several modeling methods were employed in the analysis of 102 absorption spectra, 24 of which were measured for the first time. The primary objective was to identify suitable methods that enable accurate predictions of molecular structure classifications with minimized statistical uncertainties. Rather than identifying a single, unifying method to reliably predict molecular structure contributions to VUV absorption spectra, coordination is required among a particular method, the type of molecular structure detail (e.g. conjugation), and absorption region of interest. The latter is accomplished using a binning approach, wherein absorption regions of ~0.5 eV were utilized rather than the entire ~4.8 eV range. Photon energy binning enabled analysis of region-specific predictions of accuracy, precision, and recall. The outcome from the binning approach is that, rather than utilizing the entire spectrum, optimal determination of molecular structure using machine learning methods depends on the absorption region. Furthermore, the present work provides separate machine learning models for each molecular classification, which enables the identification of multi-functional species relevant to atmospheric chemistry and combustion chemistry, where isomer-resolved speciation is critical to understanding complex reaction networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transition-metal single atoms in nitrogen-doped graphenes as efficient active centers for water splitting: a theoretical study

Highly active single-atom catalysts (SACs) have recently been intensively studied for their potential in the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER). Due to the existence of many such SAC systems, a general understanding of the trend and designing principle is necessary to discover an optimal SAC system. In this work, by using density functional theory (DFT), we investigated a series of late single transition metals (TM = Fe, Co, Ni, Cu, and Pd) anchored on various N doped graphenes (xN–TM, x = 1–4) as electrocatalysts for both the HER and OER. Solvent effects were taken into account using an implicit continuum model. Our results reveal that the catalytic activity of SACs is determined by the local coordination number of N and TM in the catalysts. Among the considered catalysts, a low-coordinated Co site, i.e. a triple-coordinated Co, exhibits a high catalytic activity toward the HER with a calculated hydrogen adsorption free energy of –0.01 eV, whereas a high-coordinated Co center, i.e. a quadruple-coordinated Co is a promising candidate for the OER with a low computed overpotential of –0.39 V, which are comparable to those of noble metal catalysts, indicating superior HER and OER performance of N–Co co-doped graphenes. The results shed light on the potential applications of TM and N co-doped graphenes as efficient single-atom bifunctional catalysts for water splitting, thereby functioning as promising candidates for hydrogen/oxygen production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Equitable Transactive Market Design to Coordinate Networked Microgrids with Mixed Ownership

This paper presents an inter-microgrid peer-topeer (P2P) transactive market mechanism to support the coordination of multiple microgrids in a mixed-ownership environment, while enabling prosumers to actively participate in the market to get their own benefits. An equitable P2P transactive energy market is designed, in which the energy burden to customers within microgrids is fairly distributed by leveraging a peer-to-peer communication network among MG owners and the distribution system operator (DSO). To reach the market settlement, a consensus-based distributed optimization algorithm is introduced to enable each MG owner and the DSO to distributedly determine the cleared price which is compensated by a household-income-based discount factor to encourage the energy-burden equity among customers in networked microgrids service territory. Numerical results on the modified 123 node test feeder including 6 microgrids are used to demonstrate the operation of the introduced equitable transactive energy market.

Vu, Thanh Long↗

Enumeration reduction algorithm for the characterization of multi-primary LED systems

Multi-primary tunable LED lighting systems can generate a vast number of spectral outputs, with the exact number depending on the resolution of the control signal and number of LED primaries. Computing all combinations to identify optimal spectral power distributions (SPDs) with a specified chromaticity would require a tremendous amount of time and computational power. Here, an enumeration reduction (ER) algorithm is described to reduce the computation time by defining a bounding pyramid in the three-dimensional tristimulus space that maps to the circumscribed square of the target region in the chromaticity diagram. This method enables computing only the necessary amount of tristimulus values (and resulting chromaticity coordinates) for SPDs that fall into a user-defined target chromaticity area, reducing computation time by avoiding the need to generate each combination and calculate its chromaticity coordinates. The results show that the proposed ER algorithm can greatly reduce the time – up to 922 times in a series of tests – to determine a set of metamers compared to a full enumeration computation.

47 OTHER INSTRUMENTATION↗

Motion and force control for multiple cooperative manipulators

The motion and force control of multiple robot arms manipulating a commonly held object is addressed. A general control paradigm that decouples the motion and force control problems is introduced. For motion control, there are three natural choices: (1) joint torques, (2) arm-tip force vectors, and (3) the acceleration of a generalized coordinate. Choice (1) allows a class of relatively model-independent control laws by exploiting the Hamiltonian structure of the open-loop system; (2) and (3) require the full model information but produce simpler problems. To resolve the nonuniqueness of the joint torques, two methods are introduced. If the arm and object models are available, the allocation of the desired end-effector control force to the joint actuators can be optimized; otherwise the internal force can be controlled about some set point. It is shown that effective force regulation can be achieved even if little model information is available.

Wen, John T.↗

Finite-difference simulation and visualization of elastodynamics in time-evolving generalized curvilinear coordinates

Modeling and simulation of free and forced structural vibrations is essential to an overall structural health monitoring capability. In the various embodiments, a first principles finite-difference approach is adopted in modeling a structural subsystem such as a mechanical gear by solving elastodynamic equations in generalized curvilinear coordinates. Such a capability to generate a dynamic structural response is widely applicable in a variety of structural health monitoring systems. This capability (1) will lead to an understanding of the dynamic behavior of a structural system and hence its improved design, (2) will generate a sufficiently large space of normal and damage solutions that can be used by machine learning algorithms to detect anomalous system behavior and achieve a system design optimization and (3) will lead to an optimal sensor placement strategy, based on the identification of local stress maxima all over the domain.

Kaul, Upender K.↗