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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Asynchronous Execution of Heterogeneous Tasks in ML-Driven HPC Workflows

Heterogeneous scientific workflows consist of numerous types of tasks that require execution on heterogeneous resources. Asynchronous execution of those tasks is crucial to improve resource utilization, task throughput and reduce workflows' makespan. Therefore, middleware capable of scheduling and executing different task types across heterogeneous resources must enable asynchronous execution of tasks. In this paper, we investigate the requirements and properties of the asynchronous task execution of machine learning (ML)-driven high-performance computing (HPC) workflows. We model the degree of asynchronicity permitted for arbitrary workflows and propose key metrics that can be used to determine qualitative benefits when employing asynchronous execution. Our experiments represent relevant scientific drivers, we perform them at scale on Summit, and we show that the performance enhancements due to asynchronous execution are consistent with our model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Use of machine learning to analyze chemistry card sort tasks

Education researchers are deeply interested in understanding the way students organize their knowledge. Card sort tasks, which require students to group concepts, are one mechanism to infer a student’s organizational strategy. However, the limited resolution of card sort tasks means they necessarily miss some of the nuance in a student’s strategy. Here in this work, we propose new machine learning strategies that leverage a potentially richer source of student thinking: free-form written language justifications associated with student sorts. Using data from a university chemistry card sort task, we use vectorized representations of language and unsupervised learning techniques to generate qualitatively interpretable clusters, which can provide unique insight in how students organize their knowledge. We compared these to machine learning analysis of the students’ sorts themselves. Machine learning-generated clusters revealed different organizational strategies than those built into the task; for example, sorts by difficulty or even discipline. There were also many more categories generated by machine learning for what we would identify as more novice-like sorts and justifications than originally built into the task, suggesting students’ organizational strategies converge when they become more expert-like. Finally, we learned that categories generated by machine learning for students’ justifications did not always match the categories for their sorts, and these cases highlight the need for future research on students’ organizational strategies, both manually and aided by machine learning. In sum, the use of machine learning to analyze results from a card sort task has helped us gain a more nuanced understanding of students’ expertise, and demonstrates a promising tool to add to existing analytic methods for card sorts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Forecasting for the Weather Driven Energy System - A New Task under IEA Wind

The energy system needs a range of forecast types for its operation in addition to the narrow wind power forecast that has been the focus of considerable recent attention. Therefore, the group behind the former IEA Wind Task 36 Forecasting for Wind Energy has initiated a new IEA Wind Task with a much broader perspective, which includes prospective interaction with other IEA Technology Collaboration Programmes such as the ones for PV, hydropower, system integration, hydrogen etc. In the new IEA Wind Task 51 (entitled "Foreacsting for the Weather Drive Energy System") the existing Work Packages (WPs) are complemented by work streams in a matrix structure. The Task is divided in three WPs according to the stakeholders: WP1 is mainly aimed at meteorologists, providing the weather forecast basis for the power forecasts. In WP2, the forecast service vendors are the main stakeholders, while the end users populate WP3. The new Task 51 started in January 2022. Planned activities include 4 workshops. The first will focus on the state of the art in forecasting for the energy system plus related research issues and be held during September 2022 in Dublin. The other three workshops will be held later during the 4-year Task period and address (1) seasonal forecasting with emphasis on Dunkelflaute, storage and hydro, (2) minute-scale forecasting, and (3) extreme power system events. The issues and conclusions of each of the workshops will be documented by a published paper. Additionally, the Recommended Practice on Forecast Solution Selection will be updated to reflect the broader perspective.

geophysics computing↗
DOE OSTI2018

Coarse-to-Fine Multi-Task Training of Convolutional Neural Networks for Automated Information Extraction from Cancer Pathology Reports

Information extraction and coding of free-text pathology reports is an important activity for cancer registries to support national cancer surveillance. Cancer registrars must process high volumes of pathology reports on an annual basis. In this study, we investigated an automated approach using a coarse-to-fine training of convolutional neural networks (CNNs) for extracting the primary site, histological grade and laterality from unstructured cancer pathology text reports. Our proposed training scheme consists of two stages. In the first stage, the multi-task learning (MTL) with hard parameter sharing approach is used to train a multi-task MT-CNN model for all the tasks. Then, the TM-CNN parameters are used to initialize a CNN model for each task to be fine trained individually using its corresponding dataset. The performance of our proposed model was compared against a state-of-the-art CNN and the commonly used SVM classifier. We observed that the proposed model consistently outperformed the base line models, especially for the less prevalent classes. Specifically, the proposed training approach achieved a micro-F score of 0.7749 over 12 ICD- O-3 topography codes which is a significant improvement as compared with state-of-the-art CNN (0.7101) and the SVM (0.6019) classifiers. Also, the results demonstrate the potential of the proposed method for handling class imbalance within each task. It significantly improves macro-F score by 24% and 12% of the primary site and histology grade tasks, respectively.

Alawad, Mohammed↗
DOE OSTI2018

Symmetric Indefinite Linear Solver Using OpenMP Task on Multicore Architectures

Recently, the Open Multi-Processing (OpenMP) standard has incorporated task-based programming, where a function call with input and output data is treated as a task. At run time, OpenMP's superscalar scheduler tracks the data dependencies among the tasks and executes the tasks as their dependencies are resolved. On a shared-memory architecture with multiple cores, the independent tasks are executed on different cores in parallel, thereby enabling parallel execution of a seemingly sequential code. With the emergence of many-core architectures, this type of programming paradigm is gaining attention-not only because of its simplicity, but also because it breaks the artificial synchronization points of the program and improves its thread-level parallelization. In this paper, we use these new OpenMP features to develop a portable high-performance implementation of a dense symmetric indefinite linear solver. Obtaining high performance from this kind of solver is a challenge because the symmetric pivoting, which is required to maintain numerical stability, leads to data dependencies that prevent us from using some common performance-improving techniques. To fully utilize a large number of cores through tasking, while conforming to the OpenMP standard, we describe several techniques. Our performance results on current many-core architectures-including Intel's Broadwell, Intel's Knights Landing, IBM's Power8, and Arm's ARMv8-demonstrate the portable and superior performance of our implementation compared with the Linear Algebra PACKage (LAPACK). The resulting solver is now available as a part of the PLASMA software package.

Computer Science↗
DOE OSTI2013

Optimization of energy window for {sup 90}Y bremsstrahlung SPECT imaging for detection tasks using the ideal observer with model-mismatch

Purpose: In yttrium-90 ({sup 90}Y) microsphere brachytherapy (radioembolization) of unresectable liver cancer, posttherapy {sup 90}Y bremsstrahlung single photon emission computed tomography (SPECT) has been used to document the distribution of microspheres in the patient and to help predict potential side effects. The energy window used during projection acquisition can have a significant effect on image quality. Thus, using an optimal energy window is desirable. However, there has been great variability in the choice of energy window due to the continuous and broad energy distribution of {sup 90}Y bremsstrahlung photons. The area under the receiver operating characteristic curve (AUC) for the ideal observer (IO) is a widely used figure of merit (FOM) for optimizing the imaging system for detection tasks. The IO implicitly assumes a perfect model of the image formation process. However, for {sup 90}Y bremsstrahlung SPECT there can be substantial model-mismatch (i.e., difference between the actual image formation process and the model of it assumed in reconstruction), and the amount of the model-mismatch depends on the energy window. It is thus important to account for the degradation of the observer performance due to model-mismatch in the optimization of the energy window. The purpose of this paper is to optimize the energy window for {sup 90}Y bremsstrahlung SPECT for a detection task while taking into account the effects of the model-mismatch. Methods: An observer, termed the ideal observer with model-mismatch (IO-MM), has been proposed previously to account for the effects of the model-mismatch on IO performance. In this work, the AUC for the IO-MM was used as the FOM for the optimization. To provide a clinically realistic object model and imaging simulation, the authors used a background-known-statistically and signal-known-statistically task. The background was modeled as multiple compartments in the liver with activity parameters independently following a Gaussian distribution; the signal was modeled as a tumor with a Gaussian-distributed activity parameter located randomly with equal probability at one of three positions. The IO test statistics (i.e., likelihood ratios) were estimated using Markov-chain Monte Carlo methods. The authors realistically modeled human anatomy using a digital phantom code, and realistically simulated {sup 90}Y bremsstrahlung SPECT imaging with a clinical SPECT system and typical imaging parameters using a previously validated Monte Carlo bremsstrahlung simulation method. Model-mismatch was included by modeling image formation process in the calculation of IO test statistics using an analytic modeling method previously developed for quantitative {sup 90}Y bremsstrahlung SPECT. To demonstrate the effects of the model-mismatch on the detection task, the authors optimized the energy window both with and without model-mismatch included in the IO. Results: For all the energy windows, the AUC values for the IO-MM were smaller than that for the IO. The optimal windows for the IO-MM and the IO were 80-180 and 60-400 keV, respectively. Conclusions: The authors have demonstrated the degradation of the ideal performance due to model-mismatch and optimized the energy window for {sup 90}Y bremsstrahlung SPECT for detection tasks by accounting for the effects of the model-mismatch. The obtained optimal window was much narrower when taking into account the model-mismatch and similar to that obtained previously for estimation tasks.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation

Purpose: Nonstationarity is an important aspect of imaging performance in CT and cone-beam CT (CBCT), especially for systems employing iterative reconstruction. This work presents a theoretical framework for both filtered-backprojection (FBP) and penalized-likelihood (PL) reconstruction that includes explicit descriptions of nonstationary noise, spatial resolution, and task-based detectability index. Potential utility of the model was demonstrated in the optimal selection of regularization parameters in PL reconstruction. Methods: Analytical models for local modulation transfer function (MTF) and noise-power spectrum (NPS) were investigated for both FBP and PL reconstruction, including explicit dependence on the object and spatial location. For FBP, a cascaded systems analysis framework was adapted to account for nonstationarity by separately calculating fluence and system gains for each ray passing through any given voxel. For PL, the point-spread function and covariance were derived using the implicit function theorem and first-order Taylor expansion according toFessler [“Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): Applications to tomography,” IEEE Trans. Image Process. 5(3), 493–506 (1996)]. Detectability index was calculated for a variety of simple tasks. The model for PL was used in selecting the regularization strength parameter to optimize task-based performance, with both a constant and a spatially varying regularization map. Results: Theoretical models of FBP and PL were validated in 2D simulated fan-beam data and found to yield accurate predictions of local MTF and NPS as a function of the object and the spatial location. The NPS for both FBP and PL exhibit similar anisotropic nature depending on the pathlength (and therefore, the object and spatial location within the object) traversed by each ray, with the PL NPS experiencing greater smoothing along directions with higher noise. The MTF of FBP is isotropic and independent of location to a first order approximation, whereas the MTF of PL is anisotropic in a manner complementary to the NPS. Task-based detectability demonstrates dependence on the task, object, spatial location, and smoothing parameters. A spatially varying regularization “map” designed from locally optimal regularization can improve overall detectability beyond that achievable with the commonly used constant regularization parameter. Conclusions: Analytical models for task-based FBP and PL reconstruction are predictive of nonstationary noise and resolution characteristics, providing a valuable framework for understanding and optimizing system performance in CT and CBCT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Neck Muscle Coactivation Response to Varied Levels of Mental Workload During Simulated Flight Tasks

Objective To evaluate neck muscle coactivation across different levels of mental workload during simulated flight tasks. Background Neck pain (NP) is highly prevalent among military aviators. Given the complex nature within the flight environment, mental workload may be a risk factor for NP. This may induce higher levels of neck muscle coactivity, which over time may accelerate fatigue, increase neck discomfort, and affect flight task performance. Method Three counterbalanced mental workload conditions represented by simulated flight tasks modulated by interstimulus frequency and complexity were investigated using the Modifiable Multitasking Environment (ModME). The primary measure was a neck coactivation index to describe the neuromuscular effort of the neck muscles as a system. Additional measures included perceived workload (NASA TLX), subjective discomfort, and task performance. Participants ( n = 60; 30M, 30F) performed three test conditions over 1 hr each while seated in a simulated seating environment. Results Neck coactivation indices (CoA) and subjective neck discomfort corresponded with increasing level of mental workload. Average CoAs for low, medium, and high workloads were: .0278(SD = .0232), .0286(SD = .0231), and .0295(SD = .0228), respectively. NASA TLX mental, temporal, effort, and overall scores also increased with the level of mental workload assigned. For ModME task performance, the overall performance score, monitoring accuracy, and resource management accuracy decreased while reaction times increased with the increasing level of mental workload. Communication accuracy was lowest with the low mental workload but had higher reaction times relative to increasing workload. Conclusion Mental workload affects neck muscle coactivation during combinations of simulated flight tasks within a simulated helicopter seating environment. Application The results of this study provide insights into the physical response to mental workload. With increasing multisensory modalities within the work environment, these insights may assist the consideration of physical effects from cognitive factors.

Behavioral Sciences↗
DOE OSTI2023

Exploiting Task Tolerances in Mimicry-based Telemanipulation

We explore task tolerances, i.e., allowable position or rotation inaccuracy, as an important resource to facilitate smooth and effective telemanipulation. Task tolerances provide a robot flexibility to generate smooth and feasible motions; however, in teleoperation, this flexibility may make the user’s control less direct. In this work, we implemented a telema nipulation system that allows a robot to autonomously adjust its configuration within task tolerances. We conducted a user study comparing a telemanipulation paradigm that exploits task tolerances (functional mimicry) to a paradigm that requires the robot to exactly mimic its human operator (exact mimicry), and assess how the choice in paradigm shapes user experience and task performance. Our results show that autonomous adjustments within task tolerances can lead to performance improvements without sacrificing perceived control of the robot. Additionally, we find that users perceive the robot to be more under control, predictable, fluent, and trustworthy in functional mimicry than in exact mimicry.

42 ENGINEERING↗
DOE OSTI2024

DECOVALEX-2023: Task D Final Report

Task D of DECOVALEX-2023 is focused on the simulation of the coupled thermal hydraulic-mechanical (THM) behaviour in the full-scale engineered barrier system (EBS). The Horonobe EBS experiment is the demonstration of the full-scale EBS in the underground research laboratory (URL) (performed by JAEA in the Horonobe URL in Japan). Task D consisted of the three steps, a preliminary step (Step 0), simulation of the laboratory tests (Step 1) and simulation of the in-situ full-scale EBS experiment (Step 2). Since the Horonobe EBS experiment demonstrates the vertical emplacement option of the EBS, the experiment gallery is also backfilled with the backfill material. Therefore, interaction between the EBS and the backfill material can also be demonstrated, such as deformation (change of density) of the buffer material. The underground water in the Horonobe URL is saline. This fact adds chemical processes to THM behaviour. For example, mechanical properties (such as swelling pressure of the buffer material and backfill material) and hydraulic properties (such as permeability of the buffer material and backfill material) change depending on the water chemistry. Task D was therefore a challenging Task focused on not only the relatively simple THM behaviour but also complex THM behaviour including chemical processes. Six research teams (BGR, CAS, JAEA, KAERI, SNL and Taipower) participated the Task D. BGR, CAS, JAEA, KAERI and Taipower research teams selected a THM approach, while the SNL research team selected a TH approach. Step 1 involved the simulation of laboratory test results and was important to check the numerical codes developed by the research teams. Step 1 was divided into four sub steps. The simulation results through the Step 1 identified the parameters for simulation of the Step 2. Basic parameters of the materials (buffer material, backfill material, rock mass, concrete, sand) were provided by JAEA. Special parameters which research team needed were identified by back analysis of Step 1. Most notably the mechanical behaviour of swelling and displacement depended on the applied model (elastic model or elastoplastic model). Parameters such as Young’s modulus were found to need smaller values than characterised in the fundamental laboratory test results (Step 1-1, 1-2) for the elastic model. Although laboratory experiments are usually simple, test results contained some error. For example, if the saturation level is 100 % or higher, it should be considered an error. This situation was presented in the Step 1-3. A possible reason is that the buffer material is a mixture of bentonite and silica sand. When a specimen is cut to measure volume or weight, sand grains will affect the measurement data. In Step 2, boundary conditions such as temperature on the surface of the simulated overpack, heater power of the electrical heaters installed in the simulated overpack, injection pressure and inflow rate of the test water, were applied. The outer boundary conditions can be selected using measured data (injection pressure and inflow rate of the test water that is controlled by the injection systems installed in the sand layer around the buffer material and in the boundary between backfill material and concrete support). Since such measured data has some noise, research teams developed their own simplified boundary conditions. Inner boundary conditions can be selected using measured data as heater power and temperature on the surface of the simulated overpack. These data also contain some noise, so research teams developed their own simplified developed boundary conditions. Task D validated various approaches thorough the simulation of the in-situ full scale EBS system including backfill of the gallery: variations in the coupling processes (THM or THC), analysis codes, and boundary conditions. Temperature distribution in the buffer material was simulated well by all research teams. This means thermal behaviour is not sensitive to the simulation approaches. Although the water content distribution on the outside of the buffer material was well simulated by all research teams, the simulation results differ from the measured values inside the buffer material (at the centre and inside, near the simulated overpack). The buffer material is made from tap water, but in the in-situ experiment, saline groundwater infiltrates the buffer material. Therefore, the selection of the hydraulic parameters of the buffer material greatly affects the simulation results of the re saturation behaviour of the buffer material. In the Horonobe EBS experiment, measured values suitable for validating the simulation results were not obtained near the simulated overpack. When simulating the pressure and deformation of the buffer material, the measurement data is easily affected by the installation conditions of the measurement sensors, so verifying the measurement data itself remains an issue. Mechanical simulation results differ depending on whether they are considered as elastic or elastoplastic phenomena. The accuracy of measured in-situ data can be assessed by detailed analysis comparing sampling specimen analysis and measured data. The Horonobe EBS experiment is scheduled to be dismantled in the future (FY2026 and 2027). This detailed dismantling investigation will finally confirm the measured data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Evaluation of Howard A. Hanson Dam Juvenile Fish Passage and Survival Study Live Fish Injury Assessment, Sensor Fish, and BioPA Modeling Tasks

The live fish injury assessment, Sensor Fish, and BioPA modeling study tasks were conducted by researchers from Pacific Northwest National Laboratory (PNNL). The four tasks were part of the larger Evaluation of Howard A. Hanson Dam (HAHD) Juvenile Fish Passage and Survival study, which had six total tasks. To achieve study objectives for each of the four tasks, field work occurred at Green Peter Dam (GPR) to evaluate the highest elevation steep slope bypass pipe, at HAHD to evaluate baseline conditions of the horseshoe tunnel, and at PNNL’s Aquatic Research Laboratory (ARL) to evaluate simulated dam passage conditions (i.e., shear forces and collision). Each of these evaluations utilized live fish injury assessment, Sensor Fish, and BioPA modeling. Live fish injury assessment and survival (tagged with and without balloon or passive integrated transponder [PIT] tags) was correlated with Sensor Fish to determine thresholds. The CFD analyses were then performed, and the computed values were compared to the corresponding measured values of Sensor Fish data. The results of the overall injury and survival of fish was also used in the validation of the CFD modeling method. Collectively, the results will aid in future modeling of fish passage at HAHD. Results from these tasks can be used by biologists, engineers, resource managers, and regional decision-makers to inform baseline conditions under current operations and the engineering design of the new FPF at HAHD. This draft report contains initial data and results from the four tasks. Table 8 1, Table 8 2, and Table 8 3, and Figure 8 1, Figure 8 2, and Figure 8 3 depict the CFD modeling findings for the GPR steep slope bypass, HAHD horseshoe tunnel, and laboratory testing. Table 8 4, Table 8 5, and Table 8 6 depict the Sensor Fish findings for the GPR steep slope bypass and HAHD horseshoe tunnel testing. The Mv values observed in the HAHD were significantly lower compared to the laboratory experiments conducted at PNNL. Currently, investigations are underway to understand the reasons for this disparity and to establish an appropriate threshold value for Mv. Survival predictions presented in the tables below should be considered preliminary and should not be used until further analyses and adjustments are completed. The next steps for modeling will include the flow regime, (i.e., density of flow regimes due to water and air mixing ) to continue to improve on the threshold value for Mv.

13 HYDRO ENERGY↗
NASA NTRS1977

Multi-attribute subjective evaluations of manual tracking tasks vs. objective performance of the human operator

A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.

Siapkaras, A.↗
NASA NTRS1977

Reduced mental capacity and behavior of a rider of a bicycle simulator under alcohol stress or under dual task load

Experiments were carried out on a bicycle simulator with alcohol administration and a binary choice task in separate sessions, intending to reduce the subject's mental capacity. Before and after such sessions a visual evoked response measurement was done. The subject's performance was analyzed with describing function techniques. The results indicate that the alcohol affects the course-following task as well as the balancing task. The binary choice task is more specifically influencing the course-following task. The dual task shows a more pronounced effect on the recovery of the evoked response. The alcohol is delaying the recovery curve of the evoked response. A tentative explanation can be given which agrees with the performance data.

Soede, M.↗
NASA NTRS1977

A model for the pilot's use of motion cues in roll-axis tracking tasks

Simulated target-following and disturbance-regulation tasks were explored with subjects using visual-only and combined visual and motion cues. The effects of motion cues on task performance and pilot response behavior were appreciably different for the two task configurations and were consistent with data reported in earlier studies for similar task configurations. The optimal-control model for pilot/vehicle systems provided a task-independent framework for accounting for the pilot's use of motion cues. Specifically, the availability of motion cues was modeled by augmenting the set of perceptual variables to include position, rate, acceleration, and accleration-rate of the motion simulator, and results were consistent with the hypothesis of attention-sharing between visual and motion variables. This straightforward informational model allowed accurate model predictions of the effects of motion cues on a variety of response measures for both the target-following and disturbance-regulation tasks.

Levison, W. H.↗
NASA NTRS1983

Measuring pilot workload in a moving-base simulator. I Asynchronous secondary choice-reaction task

The de facto method for measuring airplane pilot workload is based upon subjective ratings. While researchers agree that such subjective data should be bolstered by using objective behavioral measures, results to date have been mixed. No clear objective technique has surfaced as the metric of choice. It is believed that this difficulty is in part due to neglect of theoretical work in psychology that predicts some of the difficulties that are inherent in a futile search for 'the one and only' best secondary task to measure workload. An initial study that used both subjective ratings and an asynchronous choice-reaction secondary task was conducted to determine if such a secondary task could indeed meet the methodological constraints imposed by current theories of attention. Two variants of a flight scenario were combined with two levels of the secondary task. Appropriate single-task control conditions were also included. Results give grounds for cautious optimism but indicate that future research should use synchronous secondary tasks where possible.

Kantowitz, B. H.↗
NASA NTRS1983

An analysis of the processing requirements of a complex perceptual-motor task

Current concerns in the assessment of mental workload are discussed, and the event-related brain potential (ERP) is introduced as a promising mental-workload index. Subjects participated in a series of studies in which they were required to perform a target acquisition task while also covertly counting either auditory or visual probes. The effects of several task-difficulty manipulations on the P300 component of the ERP elicited by the counted stimulus probes were investigated. With sufficiently practiced subjects the amplitude of the P300 was found to decrease with increases in task difficulty. The second experiment also provided evidence that the P300 is selectively sensitive to task-relevant attributes. A third experiment demonstrated a convergence in the amplitude of the P300s elicited in the simple and difficult versions of the tracking task. The amplitude of the P300 was also found to covary with the measures of tracking performance. The results of the series of three experiments illustrate the sensitivity of the P300 to the processing requirements of a complex target acquisition task. The findings are discussed in terms of the multidimensional nature of processing resources.

Kramer, A. F.↗
NASA NTRS1984

New Uses for Sensitivity Analysis: How Different Movement Tasks Effect Limb Model Parameter Sensitivity

Original results for a newly developed eight-order nonlinear limb antagonistic muscle model of elbow flexion and extension are presented. A wider variety of sensitivity analysis techniques are used and a systematic protocol is established that shows how the different methods can be used efficiently to complement one another for maximum insight into model sensitivity. It is explicitly shown how the sensitivity of output behaviors to model parameters is a function of the controller input sequence, i.e., of the movement task. When the task is changed (for instance, from an input sequence that results in the usual fast movement task to a slower movement that may also involve external loading, etc.) the set of parameters with high sensitivity will in general also change. Such task-specific use of sensitivity analysis techniques identifies the set of parameters most important for a given task, and even suggests task-specific model reduction possibilities.

Winters, J. M.↗
NASA NTRS1990

Multiple task point control of a redundant manipulator

The kinematic control of a redundant arm based on multiple tasks assigned to different locations of the manipulator is presented. This is equivalent to decomposing a redundant arm into two (or more) nonredundant local arms, the basearm and the forearm, at an intermediate arm location or task point called the elbow. A redundant arm is transformed into a serially cooperating dual-arm system, with the cooperation between the local arms being carried out at the elbow. Then, a manipulator end-effector motion specified by a given task is decomposed into motions of individual local arms as well as an end-effector free motion based on achieving maximum efficiency in task execution. To consider global optimization, elbow control is applied to reshaping and reorientation of a manipulability ellipsoid at the end effector during task execution. The resolved rate control of elbow in the end-effector null and free motion space is used to maximize arm homogeneity and to match the forearm motion space with the task space. Simulation results are shown.

Lee, Sukhan↗