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At least 73 records · Page 4

Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Modeling Adaptive Cruise Control (ACC) vehicles enables the understanding of the impact of these vehicles on traffic flow. In this work, two online methods are used to provide real time system identification of ACC enabled vehicles. The first technique is a recursive least squares (RLS) approach, while the second method solves a nonlinear joint state and parameter estimation problem via particle filtering (PF). We provide a parameter identifiability analysis for both methods to analytically show that the model parameters are not identifiable using equilibrium driving. The accuracy and computational runtime of the online methods are compared to a commonly used offline simulation-based optimization (i.e., batch optimization) approach. The methods are tested on synthetic data as well as on empirical data collected directly from a 2019 model year ACC vehicle using data from sensors that are part of the stock ACC system. The online methods are scalable and provide comparable accuracy to the batch method. RLS runs in real time and is two orders of magnitude faster than the batch method for modest sized (e.g., 15 min) datasets. The particle filter also runs in real- time, and is also suitable in streaming applications in which the datasets can grow arbitrarily large.

33 ADVANCED PROPULSION SYSTEMS↗

Agreement Between Institutional Measurements and Treatment Planning System Calculations for Basic Dosimetric Parameters as Measured by the Imaging and Radiation Oncology Core-Houston

Purpose: To compare radiation machine measurement data collected by the Imaging and Radiation Oncology Core at Houston (IROC-H) with institutional treatment planning system (TPS) values, to identify parameters with large differences in agreement; the findings will help institutions focus their efforts to improve the accuracy of their TPS models. Methods and Materials: Between 2000 and 2014, IROC-H visited more than 250 institutions and conducted independent measurements of machine dosimetric data points, including percentage depth dose, output factors, off-axis factors, multileaf collimator small fields, and wedge data. We compared these data with the institutional TPS values for the same points by energy, class, and parameter to identify differences and similarities using criteria involving both the medians and standard deviations for Varian linear accelerators. Distributions of differences between machine measurements and institutional TPS values were generated for basic dosimetric parameters. Results: On average, intensity modulated radiation therapy–style and stereotactic body radiation therapy–style output factors and upper physical wedge output factors were the most problematic. Percentage depth dose, jaw output factors, and enhanced dynamic wedge output factors agreed best between the IROC-H measurements and the TPS values. Although small differences were shown between 2 common TPS systems, neither was superior to the other. Parameter agreement was constant over time from 2000 to 2014. Conclusions: Differences in basic dosimetric parameters between machine measurements and TPS values vary widely depending on the parameter, although agreement does not seem to vary by TPS and has not changed over time. Intensity modulated radiation therapy–style output factors, stereotactic body radiation therapy–style output factors, and upper physical wedge output factors had the largest disagreement and should be carefully modeled to ensure accuracy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

State-space self-tuning controllers for general multivariable stochastic systems

This paper presents a state-space approach for self-tuning control of a more general class of multivariable stochastic systems having a number of inputs equal or different from the number of outputs. The dynamic system is represented in the state-space innovation form with Luenberger's canonical structures. The model parameters and the Kalman gain are identified via either the extended least-squares algorithm or the least-squares ladder algorithm. The Kalman gain matrix and states can be estimated from the identified parameters without utilizing the standard state estimation algorithm. A long division method is introduced for finding the similarity transformation matrix.

Shieh, L. S.↗

Methods, systems, and devices for accurate signal timing of power component events

Disclosed herein are methods, systems, and devices for system event detection associated with power grid components. Methods include detecting, at a plurality of sensors, emissions from a system event associated with at least one winding of a power component. Methods also include determining, using a processor, a plurality of event parameters based, at least in part, on measurements made by the plurality of sensors, the event parameters identifying arrival times of the emissions at each of the plurality of sensors. Methods further include generating, using the processor, an output identifying an estimate of a position of the system event within the power component, the estimate being generated based, at least in part, on the arrival times identified by the plurality of event parameters.

Wu, Keshang↗

Insensitive control technology development

THe investigation of two insensitive controller synthesis techniques was reported. The finite dimensional inverse approach produces a time varying insensitive controller and/or parameter identifier by constructing inverse functions derived from a finite number of input output pair relationships. The MD/IM concept relies on the information matrix theory that was developed in the estimation and identification field. The MD/IM synthesis technique is based on the hypothesis that minimizing the information matrix will reduce system identifiability and consequently system sensitivity to uncertain parameters. The controllers designed with both techniques were evaluated on a realistic C-5A aircraft flight control problem. Results indicate that the FDI controller is more suited to trajectory type problems because of its time varying nature. The MD/IM controller performed as well as the top-rated controllers of the initial effort and has direct application to aircraft flight control problems.

Harvey, C. A.↗

Connecting Projects to Complete the In Situ Resource Utilization Paradigm

Terrain Identify specifics such as slope, rockiness, traction parameters Identify what part of ISRU needs each Physical Geotechnical Hardness, density, cohesion, etc. Identify what part of ISRU needs each (e.g., excavation needs to know hardness, density; soil processing needs to know density, cohesion; etc.)Mineral Identify specifics Identify what part of ISRU needs each Volatile Identify specifics Identify what part of ISRU needs each Atmosphere Identify specifics Identify what part of ISRU needs each Environment Identify specifics Identify what part of ISRU needs each Resource Characterization What: Develop an instrument suite to locate and evaluate the physical, mineral, and volatile resources at the lunar poles Neutron Spectrometer Near Infrared (IR) to locate subsurface hydrogen surface water Near IR for mineral identification Auger drill for sample removal down to 1 m Oven with Gas Chromatograph Mass Spectrometer to quantify volatiles present ISRU relevance: Water volatile resource characterization and subsurface material access removal Site Evaluation Resource Mapping What: Develop and utilize new data products and tools for evaluating potential exploration sites for selection and overlay mission data to map terrain, environment, and resource information e.g., New techniques applied to generate Digital Elevation Map (DEMs) at native scale of images (1mpxl)ISRU relevance: Resource mapping and estimation with terrain and environment information is needed for extraction planning Mission Planning and Operations What: Develop and utilize tools and procedures for planning mission operations and real time changes Planning tools include detailed engineering models (e.g., power and data) of surface segment systems allows evaluation of designs ISRU relevance: Allows for iterative engineering as a function of environment and hardware performance.

Paradigm↗

Parameter covariance and non-uniqueness in material model calibration using the Virtual Fields Method

Traditionally, material identification is performed using global load and displacement data from simple boundary-value problems such as uni-axial tensile and simple shear tests. More recently, however, inverse techniques such as the Virtual Fields Method (VFM) that capitalize on heterogeneous, full-field deformation data have gained popularity. In this work, we have written a VFM code in a finite-deformation framework for calibration of a viscoplastic (i.e. strain-rate dependent) material model for 304L stainless steel. Using simulated experimental data generated via finite-element analysis (FEA), we verified our VFM code and compared the identified parameters with the reference parameters input into the FEA. The identified material model parameters had surprisingly large error compared to the reference parameters, which was traced to parameter covariance and the existence of many essentially equivalent parameter sets. This parameter non-uniqueness and its implications for FEA predictions is discussed in detail. Lastly, we present two strategies to reduce parameter covariance – reduced parametrization of the material model and increased richness of the calibration data – which allow for the recovery of a unique solution.

304L stainless steel↗

Identification of Critical Process Parameters for Knife Milling and Alternative Communication Strategies

An assessment of knife milling operations was performed to identify parameters that require consideration to model wear and degradation of knife blades. A quality-by-design (QbD) paradigm was followed to identify material and feedstock attributes, and processing parameters that impact the quality attributes of the blades used in the comminution of biomass into forms compatible with downstream operations. Based on analytical and experimental observations of knife and tool wear, a QbD model is proposed that considers three wear mechanisms (erosion, abrasion, and gouging) to predict volumetric wear of knife blades and sharpness. These factors, if properly applied, provide a science-based approach to predict the mechanical efficiency of the mill as a function of feedstock properties, knife blade material properties, and processing parameters (feed rate, speed, and design parameters).

09 BIOMASS FUELS↗

Greybox Thermal Parameter Identification of Electric Machine Stators

The parameters of electric machine thermal equivalent circuit networks are difficult to predict due to material and manufacturing uncertainties. In this paper, a Greybox system identification approach is used to identify parameters of electric machine stator lumped parameter thermal networks (LPTNs). LPTNs provide a low order, computationally efficient, dynamic model of temperatures at specific locations. Second and third order LPTN model structures are defined as state space equations with stator thermal parameters to be identified. To test the Greybox electric machine stator thermal system identification, five stator motorette prototypes were constructed with controlled variations in slot fill and slot liner thickness. The variation in the motorette thermal parameters and thermal time constants are detected using the Greybox identification. Special attention is given to the impact of sampling rate and Greybox data record length on parameter estimation accuracy.

33 ADVANCED PROPULSION SYSTEMS↗

Power system model parameter conditioning tool

A power system model parameter conditioning tool including a server control processor in communication with phasor measurement unit monitored data records of multiple disturbance events, a model calibration unit providing event screening, power system model simulation, and simultaneous tuning of model parameters. The model calibration performing a simulation using default model parameters, the processor comparing the simulation results to the monitored data. If the prediction is within threshold, then terminating conditioning; else performing parameter identifiability analysis to determine differing effects of various model parameters on power system model accuracy, selecting a parameter set causing a degradation in power system model prediction, and updating the default model parameters corresponding to members of the parameter set with values selected to reduce the degradation. A method and a non-transitory computer readable medium are also disclosed.

Baone, Chaitanya Ashok↗

A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors

Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise that is caused by imperfect implementation of hardware. Identifying parameters such as gate and readout error rates is critical to these models. We use a Bayesian inference approach to identify posterior distributions of these parameters such that they can be characterized more elaborately. By characterizing the device errors in this way, we can further improve the accuracy of quantum error mitigation. Experiments conducted on IBM’s quantum computing devices suggest that our approach provides better error mitigation performance than existing techniques used by the vendor. Also, our approach outperforms the standard Bayesian inference method in some scenarios.

97 MATHEMATICS AND COMPUTING↗

Post-Calibration Uncertainty Analysis for Travel Times at a Naval Weapons Industrial Reserve Plant

The Naval Weapons Industrial Reserve Plant (NWIRP) in McGregor, Texas began manufacturing explosives in 1980 and several hazardous chemicals were discovered in lakes and streams surrounding the site in 1998. Contaminants traveled to local lakes and streams much faster than initially predicted. This research estimated contaminant travel times and identified locations where monitoring wells should be installed to yield the greatest reductions in uncertainties in travel-time predictions. To this end, groundwater and particle-tracking models for NWIRP site were built to predict hydraulic heads and contaminant travel times. Next, parameter (hydraulic conductivities) uncertainties, parameter identifiabilities, observation (hydraulic heads) worth, and predictive (contaminant travel times) uncertainties were quantified. Parameter uncertainties were reduced by up to 92%; a total of 19 of 158 parameters were at least moderately identifiable; travel-time uncertainties were reduced up to 92%. Additionally, travel-time predictions and post-calibration parameter distributions were generated using the null-space Monte Carlo (NSMC) technique. NSMC predicted that conservative tracers exited the flow system within a year, which matches with field data. Finally, an observations-worth analysis found that additional 11 more measurements would reduce travel-time uncertainties by factors from 1.04 to 4.3 over existing data if monitoring wells were installed at the suggested locations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Thermal-mechanical fatigue behavior of nickel-base superalloys

The main achievements of a 36-month research program are presented. The main objective was to gain more insight into the problem of crack growth under thermal mechanical fatigue (TMF) conditions. This program was conducted at M.I.T. for the period of September 1982 to September 1985. The program was arranged into five technical tasks. Under Task I, the literature of TMF data was reviewed. The goal was to identify the crack propagation conditions in aircraft engines (hot section) and to assess the validity of conventional fracture mechanics parameters to address TMF crack growth. The second task defined the test facilities, test specimen and the testing conditions needed to establish the effectiveness of data correlation parameters identified in Task I. Three materials (Inconel X-750, Hastelloy-X, and B-1900) were chosen for the program. Task II was accomplished in collaboration with Pratt & Whitney Aircraft engineers. Under Task III, a computerized testing system to measure the TMF behavior (LCF and CG behaviors) of various alloys systems was built. The software used to run isothermal and TMF tests was also developed. Built around a conventional servohydraulic machine, the system is capable of push-pull tests under stress or strain and temperature controlled conditions in the temperature range of 25C to 1050C. A crack propagation test program was defined and conducted under Task IV. The test variables included strain range, strain rate (frequency) and temperature. Task V correlated and generalized the Task IV data for isothermal and variable temperature conditions so that several crack propagation parameters could be compared and evaluated. The structural damage (mode of cracking and dislocation substructure) under TMF cycling was identified and contrasted with the isothermal damage to achieve a sound fundamental mechanistic understanding of TMF.

Pelloux, R. M.↗

Modal Parameter Identification of a Flexible Arm System

In this paper an experiment is designed for the modal parameter identification of a flexible arm system. This experiment uses a function generator to provide input signal and an oscilloscope to save input and output response data. For each vibrational mode, many sets of sine-wave inputs with frequencies close to the natural frequency of the arm system are used to excite the vibration of this mode. Then a least-squares technique is used to analyze the experimental input/output data to obtain the identified parameters for this mode. The identified results are compared with the analytical model obtained by applying finite element analysis.

Barrington, Jason↗

Input/output system identification - Learning from repeated experiments

The paper describes three approaches and possible variations for the determination of the Markov parameters for forced response data using general inputs. It is shown that, when the parameters in the solution procedure are bootstrapped, the results can be obtained very efficiently, but the errors propagate throughout all parameters. By arranging the data in a different form and using singular value decomposition, the resulting identified parameters are more accurate, in the least number of successive experiments, at the expense of a large matrix singular value decomposition. When a recursive procedure is employed, the calculations can be performed very efficiently, but the number of repetitions of the experiments is much greater for a given accuracy than for any of the previous approaches. An alternative formulation is proposed to combine the advantages of each of the approaches.

Juang, Jer-Nan↗

Identification of Critical Surface Parameters Driving Lectin-Mediated Capture of Bacteria from Solution

Lectin-functional interfaces are useful for isolation of bacteria from solution because they are low-cost and allow nondestructive, reversible capture. This study provides a systematic investigation of physical and chemical surface parameters that influence bacteria capture over lectin-functionalized polymer interfaces and then applies these findings to construct surfaces with significantly enhanced bacteria capture. The designer block copolymer poly(glycidyl methacrylate)-block-poly(vinyldimethyl azlactone) was used as a lectin attachment layer, and lectin coupling into the polymer film through azlactone–lectin coupling reactions was first characterized. Here, experimental parameters including polymer areal chain density, lectin molecular weight, and lectin coupling buffer were systematically varied to identify parameters driving highest azlactone conversions and corresponding lectin surface densities. To introduce physical nanostructures into the attachment layer, nanopillar arrays (NPAs) of varied heights (300 and 2100 nm) were then used to provide an underlying surface template for the functional polymer layer. Capture of Escherichia coli on lectin–polymer surfaces coated over both flat and NPA surfaces was then investigated. For flat polymer interfaces, bacteria were detected on the surface after incubation at a solution concentration of 10 3 cfu/mL, and a corresponding detection limit of 1.7 × 10 3 cfu/mL was quantified. This detection limit was 1 order of magnitude lower than control lectin surfaces functionalized with standard, carbodiimide coupling chemistry. NPA surfaces containing 300 nm tall pillars further improved the detection limit to 2.1 × 10 2 cfu/mL, but also reduced the viability of captured cells. Finally, to investigate the impact of cell surface parameters on capture, we used Agrobacterium tumefaciens cells genetically modified to allow manipulation of exopolysaccharide adhesin production levels. Statistical analysis of surface capture levels revealed that lectin surface density was the primary factor driving capture, as opposed to exopolysaccharide adhesin expression. These findings emphasize the critical importance of the synthetic interface and the development of surfaces that combine high lectin densities with tailored physical features to drive high levels of capture. These insights will aid in design of biofunctional interfaces with physicochemical surface properties favorable for capture and isolation of bacteria cells from solutions.

59 BASIC BIOLOGICAL SCIENCES↗

Optimum data utilization for parameter identification with application to lifting rotors

The work is concerned with determining the minimum quantity of data needed for achieving best possible accuracy of identified parameters in transient testing of a lifting rotor blade. Specifically, the problem is that of determining from blade flapping transients caused by blade pitch inputs the equivalent Lock number and the equivalent collective pitch setting. For a given time-dependent blade pitch input function, the running time for the test less than which insufficient parameter accuracy is obtained and more than which little accuracy improvement is achieved was calculated with the aid of the Cramer-Rao lower bound for the parameter covariance matrix.

Banerjee, D.↗

Multi-scale computational modeling of residual stress in selective laser melting with uncertainty quantification

Selective laser melting (SLM) is a powder-based additive manufacturing technique which creates parts by fusing together successive layers of powder with a laser. The quality of produced parts is highly dependent on the proper selection of processing parameters, requiring significant testing and experimentation to determine parameters for a given machine and material. Computational modeling could potentially be used to shorten this process by identifying parameters through simulation. However, simulating complete SLM builds is challenging due to the difference in scale between the size of the particles and laser used in the build and the size of the part produced. Often, continuum models are employed which approximate the powder as a continuous medium to avoid the need to model powder particles individually. While computationally expedient, continuum models require as inputs effective material properties for the powder which are often difficult to obtain experimentally. Building on previous works which have developed methods for estimating these effective properties along with their uncertainties through the use of detailed models, this work presents a part scale continuum model capable of predicting residual thermal stresses in an SLM build with uncertainty estimates. Model predictions are compared to experimental measurements from the literature.

42 ENGINEERING↗