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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 OSTI2012

Transport Test Problems for Radiation Detection Scenarios

Modeling forms an important component of radiation detection development, allowing for testing of new detector designs, evaluation of existing equipment against a wide variety of potential threat sources, and assessing operation performance of radiation detection systems. This can, however, result in large and complex scenarios which are time consuming to model. A variety of approaches to radiation transport modeling exist with complementary strengths and weaknesses for different problems. This variety of approaches, and the development of promising new tools (such as ORNL’s ADVANTG) which combine benefits of multiple approaches, illustrates the need for a means of evaluating or comparing different techniques for radiation detection problems. This report presents a set of 9 test problems for comparing different types of radiation transport calculations, identifying appropriate tools for classes of problems, and testing and guiding the development of new methods. Cases are drawn primarily from existing or previous calculations with a preference for cases which include experimental data, or otherwise have results with a high level of confidence, are non-sensitive, and represent problem sets of interest to NA-22. From a technical perspective, cases are chosen to span a range of difficulty and to include gamma transport, neutron transport, or both and represent different important physical processes and a range of sensitivity to angular or energy fidelity. Following test case identification, existing information about geometry, measurements, and previous calculations were assembled. Monte Carlo results (MCNP decks) were reviewed or created and re-run in order to attain accurate computational times and to verify agreement with experimental data, when present. Test case information was then conveyed to ORNL in order to guide testing and development of hybrid calculations. The results of those ADVANTG calculations were then sent to PNNL for compilation. This is a report describing the details of the selected test cases and results from available transport codes. Additional results from other transport codes will be added during the next year, along with additional cases if needed for software testing. Future work will extend the test problems to include more extensive cross-code comparisons as well as more refined metrics for evaluating the tradeoffs between operator time, computational time, and solution accuracy, to assemble a formalized benchmark set.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Production Application Performance Data Streaming for System Monitoring

In this article, we present an approach to streaming collection of application performance data. Practical application performance tuning and troubleshooting in production high-performance computing (HPC) environments requires an understanding of how applications interact with the platform, including (but not limited to) parallel programming libraries such as Message Passing Interface (MPI). Several profiling and tracing tools exist that collect heavy runtime data traces either in memory (released only at application exit) or on a file system (imposing an I/O load that may interfere with the performance being measured). Although these approaches are beneficial in development stages and post-run analysis, a systemwide and low-overhead method is required to monitor deployed applications continuously. This method must be able to collect information at both the application and system levels to yield a complete performance picture. In our approach, an application profiler collects application event counters. A sampler uses an efficient inter-process communication method to periodically extract the application counters and stream them into an infrastructure for performance data collection. We implement a tool-set based on our approach and integrate it with the Lightweight Distributed Metric Service (LDMS) system, a monitoring system used on large-scale computational platforms. LDMS provides the infrastructure to create and gather streams of performance data in a low overhead manner. We demonstrate our approach using applications implemented with MPI, as it is one of the most common standards for the development of large-scale scientific applications. We utilize our tool-set to study the impact of our approach on an open source HPC application, Nalu. Our tool-set enables us to efficiently identify patterns in the behavior of the application without source-level knowledge. We leverage LDMS to collect system-level performance data and explore the correlation between the system and application events. Finally, we demonstrate how our tool-set can help detect anomalies with a low latency. We run tests on two different architectures: a system enabled with Intel Xeon Phi and another system equipped with Intel Xeon processor. Our overhead study shows our method imposes at most 0.5% CPU usage overhead on the application in realistic deployment scenarios.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Flat and Level Analysis Tool (FLAT) for real-time automated segmentation and analysis of concrete slab point clouds

In the United States, the flatness and levelness of concrete floors during construction is traditionally specified by a maximum allowable gap under a 3 meter straightedge. However, the straightedge method is inexact and rarely representative of the entire floor since the technician is free to choose any location on the floor to perform the measurement. In cases requiring a higher degree of precision and repeatability, concrete floor flatness and levelness can be measured using the standard test method ASTM E1155. With the recent introduction of advanced surveying instruments such as robotic theodolites and terrestrial laser scanners (TLS), the means now exist to modernize and expedite the measurement of floor flatness and levelness. This paper details the development and demonstration of a digital tool, named the Flat and Level Analysis Tool (FLAT), to automate and expedite the segmentation and analysis of flatness and levelness from dense point cloud data of concrete floor slabs. Segmentation algorithms were developed using unsupervised machine learning to extract the set of points belonging to the concrete floor slab from a full 360 scan of a construction site. After segmentation, automated analysis algorithms report the results according to the standard method. The developed algorithms were demonstrated on a dense point cloud captured from a concrete slab-on-grade at a construction site. Results show that the digital tool can quickly provide estimates for floor flatness and levelness with minimal human involvement with comparable accuracy to manual methods.

Hayes, Nolan↗
DOE OSTI2015

An efficient method for energy levels calculation using full symmetry and exact kinetic energy operator: Tetrahedral molecules

A simultaneous use of the full molecular symmetry and of an exact kinetic energy operator (KEO) is of key importance for accurate predictions of vibrational levels at a high energy range from a potential energy surface (PES). An efficient method that permits a fast convergence of variational calculations would allow iterative optimization of the PES parameters using experimental data. In this work, we propose such a method applied to tetrahedral AB{sub 4} molecules for which a use of high symmetry is crucial for vibrational calculations. A symmetry-adapted contracted angular basis set for six redundant angles is introduced. Simple formulas using this basis set for explicit calculation of the angular matrix elements of KEO and PES are reported. The symmetric form (six redundant angles) of vibrational KEO without the sin(q){sup −2} type singularity is derived. The efficient recursive algorithm based on the tensorial formalism is used for the calculation of vibrational matrix elements. A good basis set convergence for the calculations of vibrational levels of the CH{sub 4} molecule is demonstrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Improving Comfort in Hot-Humid Climates with a Whole-House Dehumidifier, Windermere, Florida [Fact Sheet]

Maintaining comfort in a home can be challenging in hot-humid climates. At the common summer temperature set point of 75°F, the perceived air temperature can vary by 11°F because higher indoor humidity reduces comfort. Often the air conditioner (AC) thermostat set point is lower than the desirable cooling level to try to increase moisture removal so that the interior air is not humid or "muggy." However, this method is not always effective in maintaining indoor relative humidity (RH) or comfort. In order to quantify the performance of a combined whole-house dehumidifier (WHD) AC system, researchers from the U.S. Department of Energy's Building America team Consortium of Advanced Residential Buildings (CARB) monitored the operation of two Lennox AC systems coupled with a Honeywell DH150 TrueDRY whole-house dehumidifier for a six-month period. By using a WHD to control moisture levels (latent cooling) and optimizing a central AC to control temperature (sensible cooling), improvements in comfort can be achieved while reducing utility costs. Indoor comfort for this study was defined as maintaining indoor conditions at below 60% RH and a humidity ratio of 0.012 lbm/lbm while at common dry bulb set point temperatures of 74°-80°F. In addition to enhanced comfort, controlling moisture to these levels can reduce the risk of other potential issues such as mold growth, pests, and building component degradation. Because a standard AC must also reduce dry bulb air temperature in order to remove moisture, a WHD is typically needed to support these latent loads when sensible heat removal is not desired.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Improved Data Interpretation through Identification of Time Series Periodicity Changes

Analysis and interpretation of time series data is easiest when the data values occur at uniform intervals in time, but actual data may have differing data sampling frequencies, such as monthly and daily readings. Applying data analysis techniques, such as smoothing, to such a data set may not give a representative result between time segments. The ability to automatically distinguish time segments of differing data frequency would provide a means for applying data analysis independently to each segment, though a suitable blending at segment boundaries would be required. A method for detecting frequency changes was developed and applied to Gaussian and median smoothing of hydraulic head data from groundwater wells at the U.S. Department of Energy Hanford Site in southeastern Washington state. The process identifies time segments of high-frequency (daily) or low-frequency (greater than daily) data using adjusted-bandwidth Gaussian kernel density estimation and a threshold value, which are further refined to address small blocks of low-frequency data within larger blocks of high-frequency data. User-selectable levels of smoothing are then applied independently to the time segments prior to combining the segment results for a single smoothed data set. This time segment identification approach provides effective low- and high-frequency data separation, which provides a method to apply data analysis independently to each time segment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Radiation Detection Computational Benchmark Scenarios

Modeling forms an important component of radiation detection development, allowing for testing of new detector designs, evaluation of existing equipment against a wide variety of potential threat sources, and assessing operation performance of radiation detection systems. This can, however, result in large and complex scenarios which are time consuming to model. A variety of approaches to radiation transport modeling exist with complementary strengths and weaknesses for different problems. This variety of approaches, and the development of promising new tools (such as ORNL’s ADVANTG) which combine benefits of multiple approaches, illustrates the need for a means of evaluating or comparing different techniques for radiation detection problems. This report presents a set of 9 benchmark problems for comparing different types of radiation transport calculations, identifying appropriate tools for classes of problems, and testing and guiding the development of new methods. The benchmarks were drawn primarily from existing or previous calculations with a preference for scenarios which include experimental data, or otherwise have results with a high level of confidence, are non-sensitive, and represent problem sets of interest to NA-22. From a technical perspective, the benchmarks were chosen to span a range of difficulty and to include gamma transport, neutron transport, or both and represent different important physical processes and a range of sensitivity to angular or energy fidelity. Following benchmark identification, existing information about geometry, measurements, and previous calculations were assembled. Monte Carlo results (MCNP decks) were reviewed or created and re-run in order to attain accurate computational times and to verify agreement with experimental data, when present. Benchmark information was then conveyed to ORNL in order to guide testing and development of hybrid calculations. The results of those ADVANTG calculations were then sent to PNNL for compilation. This is a report describing the details of the selected Benchmarks and results from various transport codes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A Data-Driven Framework for Power System Event Type Identification via Safe Semi-Supervised Techniques

Herein this paper investigates the use of phasor measurement unit (PMU) data with deep learning techniques to construct real-time event identification models for transmission networks. Increasing penetration of distributed energy resources represents a great opportunity to achieve decarbonization, as well as challenges in systematic situational awareness. When high-resolution PMU data and sufficient manually recorded event labels are available, the power event identification problem is defined as a statistical classification problem that can be solved by numerous cutting-edge classifiers. However, in real grids, collecting tremendous high-quality event labels is quite expensive. Utilities frequently have a large number of event records without in-depth details (i.e., unlabeled events). To bridge this gap, we propose a novel semi-supervised learning-based method to improve the performance of event classifiers trained with a limited number of labeled events by exploiting the information from massive unlabeled events. In other words, compared to existing data-driven methods, our method requires only a small portion of labeled data to achieve a similar level of accuracy. Meanwhile, this work discusses and addresses the performance degradation caused by class distribution mismatch between the training set and the real applications. Based on the proposed safe learning mechanism, our model does not directly use all unlabeled events during model training, but selectively uses them through a comprehensive evaluation procedure. Numerical studies on a sizable PMU dataset have been used to validate the performance of the proposed method.

42 ENGINEERING↗
DOE OSTI2014

A theoretical investigation of the (0001) covellite surfaces

We report on the properties of the (0001) covellites surfaces, which we investigate by periodic slab density functional theory calculations. The absolute surface energies have been computed for all bulk terminations, showing that surfaces terminated by the flat CuS layer are associated with the lowest surface energy. Cleavage is predicted to occur across the [0001] interlayer Cu–S bond. The surfaces obtained by lowest energy cleavage are analyzed in terms of the atomic vertical relaxation, workfunction, and surface band structure. Our study predicts the presence of a shallow p{sub z}-derived surface state located 0.26 eV below the Fermi level, which is set to play an important role in the surface reactivity of covellite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

A Phase I/II Trial of Intensity Modulated Radiation (IMRT) Dose Escalation With Concurrent Fixed-dose Rate Gemcitabine (FDR-G) in Patients With Unresectable Pancreatic Cancer

Purpose: Local failure in unresectable pancreatic cancer may contribute to death. We hypothesized that intensification of local therapy would improve local control and survival. The objectives were to determine the maximum tolerated radiation dose delivered by intensity modulated radiation with fixed-dose rate gemcitabine (FDR-G), freedom from local progression (FFLP), and overall survival (OS). Methods and Materials: Eligibility included pathologic confirmation of adenocarcinoma, radiographically unresectable, performance status of 0-2, absolute neutrophil count of {>=}1500/mm{sup 3}, platelets {>=}100,000/mm{sup 3}, creatinine <2 mg/dL, bilirubin <3 mg/dL, and alanine aminotransferase/aspartate aminotransferase {<=}2.5 Multiplication-Sign upper limit of normal. FDR-G (1000 mg/m{sup 2}/100 min intravenously) was given on days -22 and -15, 1, 8, 22, and 29. Intensity modulated radiation started on day 1. Dose levels were escalated from 50-60 Gy in 25 fractions. Dose-limiting toxicity was defined as gastrointestinal toxicity grade (G) {>=}3, neutropenic fever, or deterioration in performance status to {>=}3 between day 1 and 126. Dose level was assigned using TITE-CRM (Time-to-Event Continual Reassessment Method) with the target dose-limiting toxicity (DLT) rate set to 0.25. Results: Fifty patients were accrued. DLTs were observed in 11 patients: G3/4 anorexia, nausea, vomiting, and/or dehydration (7); duodenal bleed (3); duodenal perforation (1). The recommended dose is 55 Gy, producing a probability of DLT of 0.24. The 2-year FFLP is 59% (95% confidence interval [CI]: 32-79). Median and 2-year overall survival are 14.8 months (95% CI: 12.6-22.2) and 30% (95% CI 17-45). Twelve patients underwent resection (10 R0, 2 R1) and survived a median of 32 months. Conclusions: High-dose radiation therapy with concurrent FDR-G can be delivered safely. The encouraging efficacy data suggest that outcome may be improved in unresectable patients through intensification of local therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Tapping the treasure trove of atypical phages

With advancements in genomics technologies, a vast diversity of ‘atypical’ phages, that is, with single-stranded DNA or RNA genomes, are being uncovered from different ecosystems. Though these efforts have revealed the existence and prevalence of these nonmodel phages, computational approaches often fail to associate these phages with their specific bacterial host(s), while the lack of methods to isolate these phages has limited our ability to characterize infectivity pathways and new gene function. In this review, we call for the development of generalizable experimental methods to better capture this understudied viral diversity via isolation and study them through gene-level characterization and engineering. Establishing a diverse set of new ‘atypical’ phage model systems has the potential to provide many new biotechnologies, including potential uses of these atypical phages in halting the spread of antibiotic resistance and engineering of microbial communities for beneficial outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

SHαDE: survey description and mass–kinematics scaling relations for dwarf galaxies

ABSTRACT The Study of H α from Dwarf Emissions (SHαDE) is a high spectral resolution (R = 13 500) H α integral field survey of 69 dwarf galaxies with stellar masses 106 < M⋆ < 109 M⊙. The survey used FLAMES on the ESO Very Large Telescope. SHαDE is designed to study the kinematics and stellar populations of dwarf galaxies using consistent methods applied to massive galaxies and at matching level of detail, connecting these mass ranges in an unbiased way. In this paper, we set out the science goals of SHαDE, describe the sample properties, outline the data reduction, and analysis processes. We investigate the log M⋆–log S0.5 mass–kinematics scaling relation, which has previously shown potential for combining galaxies of all morphologies in a single scaling relation. We extend the scaling relation from massive galaxies to dwarf galaxies, demonstrating this relation is linear down to a stellar mass of M⋆ ∼ 108.6 M⊙. Below this limit, the kinematics of galaxies inside one effective radius appears to be dominated by the internal velocity dispersion limit of the H α-emitting gas, giving a bend in the log M⋆–log S0.5 relation. Replacing stellar mass with total baryonic mass using gas mass estimate reduces the severity but does not remove the linearity limit of the scaling relation. An extrapolation to estimate the galaxies’ dark matter halo masses, yields a log Mh–log S0.5 scaling relation that is free of any bend, has reduced curvature over the whole mass range, and brings galaxies of all masses and morphologies on to the virial relation.

Barat, Dilyar↗
DOE OSTI2019

Level-set Modeling Simulations of Chemical Vapor Infiltration for Ceramic Matrix Composites Manufacturing

Silicon-carbide (SiC) reinforced ceramic matrix composites (CMCs) are a key enabling technology to reduce fuel consumption and emissions of gas turbine engines. In one manufacturing approach, chemical vapor infiltration (CVI) is limited to only coating SiC fibers. The preform is then fabricated using a lay-up of basic plys or 2-D woven sheets composed of the precoated fibers. At the other extreme, CVI is used to completely densify a 3-D woven preform shaped almost like the gas turbine component itself. The latter approach is more suitable for highly engineered components which sit directly in the gas path of the engine, for example, a high pressure turbine blade. In this case, the geometry is necessarily complex for aerodynamic, stress, and lifing (multi-physics) requirements. Presently, optimizing the CVI-dominated manufacturing approach is largely by trial-and-error. In this work, a first-principles modeling of CVI is performed to realize optimization of SiC/SiC CMC manufacturing. The modeling is based on a level-set framework to describe the interface between the vapor and solid phases. A finite-difference numerical scheme using an immersed boundary method is developed for fixed, structured meshes. Massively parallel direct numerical simulations (DNS) of CVI through fiber-woven geometries are performed using one-step chemistry, and over a range of Thiele moduli. Illustrative applications of the resulting large DNS data sets are given, including the development of fiber-weave specific infiltration models and structure functions for mean-field (porous media) Computational Fluid Dynamics (CFD) simulations of CVI.

36 MATERIALS SCIENCE↗
DOE OSTI2013

NREL Controllable Grid Interface for Testing MW-Scale Wind Turbine Generators (Poster)

In order to understand the behavior of wind turbines experiencing grid disturbances, it is necessary to perform a series of tests and accurate transient simulation studies. The latest edition of the IEC 61400-21 standard describes methods for such tests that include low voltage ride-through (LVRT), active power set-point control, ramp rate limitations, and reactive power capability tests. The IEC methods are being widely adopted on both national and international levels by wind turbine manufacturers, certification authorities, and utilities. On-site testing of wind turbines might be expensive and time consuming since it requires both test equipment transportation and personnel presence in sometimes remote locations for significant periods of time because such tests need to be conducted at certain wind speed and grid conditions. Changes in turbine control software or design modifications may require redoing of all tests. Significant cost and test-time reduction can be achieved if these tests are conducted in controlled laboratory environments that replicate grid disturbances and simulation of wind turbine interactions with power systems. Such testing capability does not exist in the United States today. An initiative by NREL to design and construct a 7-MVA grid simulator to operate with the existing 2.5 MW and new upcoming 5-MW dynamometer facilities will fulfill this role and bring many potential benefits to the U.S. wind industry with the ultimate goal of reducing wind energy integration costs.

17 WIND ENERGY↗
DOE OSTI2020

Propagating sample variance uncertainties in redshift calibration: simulations, theory, and application to the COSMOS2015 data

ABSTRACT Cosmological analyses of galaxy surveys rely on knowledge of the redshift distribution of their galaxy sample. This is usually derived from a spectroscopic and/or many-band photometric calibrator survey of a small patch of sky. The uncertainties in the redshift distribution of the calibrator sample include a contribution from shot noise, or Poisson sampling errors, but, given the small volume they probe, they are dominated by sample variance introduced by large-scale structures. Redshift uncertainties have been shown to constitute one of the leading contributions to systematic uncertainties in cosmological inferences from weak lensing and galaxy clustering, and hence they must be propagated through the analyses. In this work, we study the effects of sample variance on small-area redshift surveys, from theory to simulations to the COSMOS2015 data set. We present a three-step Dirichlet method of resampling a given survey-based redshift calibration distribution to enable the propagation of both shot noise and sample variance uncertainties. The method can accommodate different levels of prior confidence on different redshift sources. This method can be applied to any calibration sample with known redshifts and phenotypes (i.e. cells in a self-organizing map, or some other way of discretizing photometric space), and provides a simple way of propagating prior redshift uncertainties into cosmological analyses. As a worked example, we apply the full scheme to the COSMOS2015 data set, for which we also present a new, principled SOM algorithm designed to handle noisy photometric data. We make available a catalogue of the resulting resamplings of the COSMOS2015 galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Benchmarking the extraction of statistical neutron capture cross sections on short-lived nuclei for applications using the β -Oslo method

Numerous scientific fields including astrophysics, nuclear power, and nuclear forensics require a knowledge of basic nuclear properties for large numbers of short-lived, radioactive isotopes far removed from stable nuclei. Neutron-capture cross sections are one such piece of nuclear data where direct measurements are not possible and theoretical predictions can vary by orders of magnitude. A recently developed indirect technique for inferring neutron capture rates, the β-Oslo method, has been introduced but not compared against a known, directly measured neutron capture cross section. To provide this benchmark, two indirect methods based on β decay and charged-particle reactions were used to extract the nuclear level density and γ-ray strength function of 51 Ti. The nuclear level density and γ-ray strength function from the two data sets were found to be equivalent and were used to extract the neutron capture cross section of 50 Ti which agrees with previous direct measurements at high neutron energies. Here, the results demonstrate the validity of the β-Oslo method for extracting neutron capture cross sections of short-lived nuclei and provide a sufficiently small uncertainty to be used in various applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Theoretical studies for the N{sub 2}–N{sub 2}O van der Waals complex: The potential energy surface, intermolecular vibrations, and rotational transition frequencies

Theoretical studies of the potential energy surface (PES) and bound states are performed for the N{sub 2}–N{sub 2}O van der Waals (vdW) complex. A four-dimensional intermolecular PES is constructed at the level of single and double excitation coupled-cluster method with a non-iterative perturbation treatment of triple excitations [CCSD(T)] with aug-cc-pVTZ basis set supplemented with bond functions. Two equivalent T-shaped global minima are located, in which the O atom of N{sub 2}O monomer is near the N{sub 2} monomer. The intermolecular fundamental vibrational states are assigned by inspecting the orientation of the nodal surface of the wavefunctions. The calculated frequency for intermolecular disrotation mode is 23.086 cm{sup −1}, which is in good agreement with the available experimental data of 22.334 cm{sup −1}. A negligible tunneling splitting with the value of 4.2 MHz is determined for the ground vibrational state and the tunneling splitting increases as the increment of the vibrational frequencies. Rotational levels and transition frequencies are calculated for both isotopomers {sup 14}N{sub 2}–N{sub 2}O and {sup 15}N{sub 2}–N{sub 2}O. The accuracy of the PES is validated by the good agreement between theoretical and experimental results for the transition frequencies and spectroscopic parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multimodal parameter spaces of a complex multi-channel neuron model

One of the most common types of models that helps us to understand neuron behavior is based on the Hodgkin–Huxley ion channel formulation (HH model). A major challenge with inferring parameters in HH models is non-uniqueness: many different sets of ion channel parameter values produce similar outputs for the same input stimulus. Such phenomena result in an objective function that exhibits multiple modes (i.e., multiple local minima). This non-uniqueness of local optimality poses challenges for parameter estimation with many algorithmic optimization techniques. HH models additionally have severe non-linearities resulting in further challenges for inferring parameters in an algorithmic fashion. To address these challenges with a tractable method in high-dimensional parameter spaces, we propose using a particular Markov chain Monte Carlo (MCMC) algorithm, which has the advantage of inferring parameters in a Bayesian framework. The Bayesian approach is designed to be suitable for multimodal solutions to inverse problems. We introduce and demonstrate the method using a three-channel HH model. We then focus on the inference of nine parameters in an eight-channel HH model, which we analyze in detail. We explore how the MCMC algorithm can uncover complex relationships between inferred parameters using five injected current levels. The MCMC method provides as a result a nine-dimensional posterior distribution, which we analyze visually with solution maps or landscapes of the possible parameter sets. The visualized solution maps show new complex structures of the multimodal posteriors, and they allow for selection of locally and globally optimal value sets, and they visually expose parameter sensitivities and regions of higher model robustness. We envision these solution maps as enabling experimentalists to improve the design of future experiments, increase scientific productivity and improve on model structure and ideation when the MCMC algorithm is applied to experimental data.

97 MATHEMATICS AND COMPUTING↗