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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 OSTI2022

Hydrogen Crossover Flux through Two-Dimensional Nanomaterials

Energy storage and conversion devices require an ion-exchange membrane with high transmission of charge-balancing ions and separation of anode and cathode electrolytes/gases. This ensures optimum device performance. Most conventional membranes suffer huge cross-permeation resulting in low energy efficiency and material degradation. This work investigated hydrogen permeability and proton transmission through membrane electrode assemblies (MEAs) containing a monolayer of hexagonal boron nitride and single-layer and bi-layer graphene in a gas-phase small-scale cell and a liquid cell. Here we found that the hydrogen crossover flux through MEAs with 2D materials was inhibited by at least a factor of 5 compared to the one without. Single-layer graphene and boron nitride enabled high proton transmission, but bi-layer graphene inhibited proton conduction. Defect visualization of 2D materials revealed few atomic-scale defects in graphene. These findings suggest that a monolayer of 2D material may provide good selectivity for energy conversion and storage devices by blocking species crossover while allowing high proton transmission.

2D materials↗
DOE OSTI2017

Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

High performance computers have for many years been on a trajectory that gives them extraordinary compute power with the addition of more and more compute cores. At the same time, other system parameters such as the amount of memory per core and bandwidth to storage have remained constant or have barely increased. This creates an imbalance in the computer, giving it the ability to compute a lot of data that it cannot reasonably save out due to time and storage constraints. While technologies have been invented to mitigate this problem (burst buffers, etc.), software has been adapting to employ in situ libraries which perform data analysis and visualization on simulation data while it is still resident in memory. This avoids the need to ever have to pay the costs of writing many terabytes of data files. Instead, in situ enables the creation of more concentrated data products such as statistics, plots, and data extracts, which are all far smaller than the full-sized volume data. With the increasing popularity of in situ, multiple in situ infrastructures have been created, each with its own mechanism for integrating with a simulation. To make it easier to instrument a simulation with multiple in situ infrastructures and include custom analysis algorithms, this project created the SENSEI framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Integrated System and Application Continuous Performance Monitoring and Analysis Capability

Scientific applications run on high-performance computing (HPC) systems are critical for many national security missions within Sandia and the NNSA complex. However, these applications often face performance degradation and even failures that are challenging to diagnose. To provide unprecedented insight into these issues, the HPC Development, HPC Systems, Computational Science, and Plasma Theory & Simulation departments at Sandia crafted and completed their FY21 ASC Level 2 milestone entitled "Integrated System and Application Continuous Performance Monitoring and Analysis Capability." The milestone created a novel integrated HPC system and application monitoring and analysis capability by extending Sandia's Kokkos application portability framework, Lightweight Distributed Metric Service (LDMS) monitoring tool, and scalable storage, analysis, and visualization pipeline. The extensions to Kokkos and LDMS enable collection and storage of application data during run time, as it is generated, with negligible overhead. This data is combined with HPC system data within the extended analysis pipeline to present relevant visualizations of derived system and application metrics that can be viewed at run time or post run. This new capability was evaluated using several week-long, 290-node runs of Sandia's ElectroMagnetic Plasma In Realistic Environments ( EMPIRE ) modeling and design tool and resulted in 1TB of application data and 50TB of system data. EMPIRE developers remarked this capability was incredibly helpful for quickly assessing application health and performance alongside system state. In short, this milestone work built the foundation for expansive HPC system and application data collection, storage, analysis, visualization, and feedback framework that will increase total scientific output of Sandia's HPC users.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Integrated System and Application Continuous Performance Monitoring and Analysis Capability (Final)

Scientific applications run on high-performance computing (HPC) systems are critical for many national security missions within Sandia and the NNSA complex. However, these applications often face performance degradation and even failures that are challenging to diagnose. To provide unprecedented insight into these issues, the HPC Development, HPC Systems, Computational Science, and Plasma Theory & Simulation departments at Sandia crafted and completed their FY21 ASC Level 2 milestone entitled "Integrated System and Application Continuous Performance Monitoring and Analysis Capability." The milestone created a novel integrated HPC system and application monitoring and analysis capability by extending Sandia’s Kokkos application portability framework, Lightweight Distributed Metric Service (LDMS) monitoring tool, and scalable storage, analysis, and visualization pipeline. The extensions to Kokkos and LDMS enable collection and storage of application data during run time, as it is generated, with negligible overhead. This data is combined with HPC system data within the extended analysis pipeline to present relevant visualizations of derived system and application metrics that can be viewed at run time or post run. This new capability was evaluated using several week-long, 290-node runs of Sandia’s ElectroMagnetic Plasma In Realistic Environments (EMPIRE) modeling and design tool and resulted in 1TB of application data and 50TB of system data. EMPIRE developers remarked this capability was incredibly helpful for quickly assessing application health and performance alongside system state. In short, this milestone work built the foundation for expansive HPC system and application data collection, storage, analysis, visualization, and feedback framework that will increase total scientific output of Sandia’s HPC users.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Quality Control of Silicon Sensor Modules for Particle Detectors

The High-Luminosity Large Hadron Collider (HL-LHC) will produce a higher rate of particle collisions than the current Large Hadron Collider (LHC), requiring important upgrades to the Compact Muon Solenoid (CMS) to handle an increased amount of data. An important upgrade is the Phase-2 Outer Tracker Upgrade, which consists of 13,000 silicon sensor modules made of two parallel silicon sensors and readout electronics. These modules undergo careful quality control checks both during and after module assembly to ensure precise and reliable detector performance. This project focuses on precision testing for quality control of silicon sensor modules at Fermilab. Hands-on work includes visual inspection, current-voltage testing, module testing, and ultraviolet (UV) light exposure of modules showing abnormal current-voltage behavior. The ultraviolet exposure process improves the abnormal sensor readout data by placing the selected sensor side of the module directly under the UV light inside a controlled box. In addition to laboratory testing and ultraviolet experiments, I developed a Python-based data tool that connects to a module database and allows selected testing conditions and module information to be retrieved and displayed efficiently. These different testing procedures, experimental processes, and computational tools support the broader goal of identifying module issues and improving modules that will be used in the CMS Outer Tracker Phase-2 Upgrade.

Siddiqui, Hooriya [DuPage Coll.] (ORCID:0009000151↗
NASA NTRS2011

Meteor Shower Activity Derived from "Meteor Watching Public-Campaign" in Japan

We tried to analyze activities of meteor showers from accumulated data collected by public campaigns for meteor showers which were performed as outreach programs. The analyzed campaigns are Geminids (in 2007 and 2009), Perseids (in 2008 and 2009), Quadrantids (in 2009) and Orionids (in 2009). Thanks to the huge number of reports, the derived time variations of the activities of meteor showers is very similar to those obtained by skilled visual observers. The values of hourly rates are about one-fifth (Geminids 2007) or about one-fourth (Perseids 2008) compared with the data of skilled observers, mainly due to poor observational sites such as large cities and urban areas, together with the immature skill of participants in the campaign. It was shown to be highly possible to estimate time variation in the meteor shower activity from our campaign.

Sato, M.↗
NASA NTRSDate not supplied

Coolant Leak from ISS External Active Thermal Control System (EATCS) – An Examination of Most Probable

The Port (P1) and Starboard (S1) External Active Thermal Control Systems (EATCS) are single phase, mechanically pumped ammonia loops that operate independently to cool majority of the hardware and payloads onboard the International Space Station (ISS). A slow ammonia leak was detected using pressure and quantity telemetry five years after the P1 EATCS was activated. The leak gradually accelerated to a rate that locating and isolating the leak became imperative to maintain cooling capability. Partial pressure measurements from the Robotic External Leak Locator (RELL) scan surveys narrowed the search to the supply and return jumpers connecting one of three radiators to the system. Subsequently, the ISS crew performed high-definition video surveys during an Extravehicular Activity (EVA), or spacewalk, and ammonia flakes were observed projecting from the jumpers. Thus, the ground teams were confident that the culprit of the ammonia leak were the jumpers. The ammonia leak stopped after ground teams remotely isolated and vented those jumpers and associated radiator. Both jumpers were removed and returned to the ground, and a root cause investigation was conducted. A calibrated leak test determined the bulk of the ammonia leaked through a pair of seals in a Quick Disconnect (QD), or connector, on one end of the return jumper. The return jumper QD was dissected, visually inspected, chemically tested and evaluated. The results indicated the most probable cause of the accelerating ammonia leak was due to defective seals, plating delamination underneath the seals, and on-orbit thermal cycles exacerbating the delamination. Both jumpers were refurbished, relaunched to the ISS, and scheduled to be reinstalled during an EVA in 2022. It appeared the issue was unique, but recently the S1 EATCS is showing signs of an accelerating ammonia leak, and RELL scans narrowed the source to a similar pair of radiator jumpers.

Darnell Cowan↗
DOE OSTI2026

Quality Control of Silicon Sensor Modules for Particle Detectors

The High-Luminosity Large Hadron Collider (HL-LHC) will produce a higher rate of particle collisions than the current Large Hadron Collider (LHC), requiring significant upgrades to the Compact Muon Solenoid (CMS) to handle the increased amount of data. An important upgrade is the Phase-2 Outer Tracker Upgrade, which consists of 13,000 silicon sensor modules made of two parallel silicon sensors and readout electronics. These modules undergo careful quality control checks both during and after module assembly to ensure precise and reliable detector performance. This project focuses on precision testing for quality control of silicon sensor modules at Fermilab. Hands-on work includes visual inspection, current-voltage testing, module testing, and ultraviolet (UV) light exposure of modules showing abnormal current-voltage behavior. The ultraviolet exposure process improves the abnormal sensor readout data by placing the selected sensor side of the module directly under the UV light inside a controlled box. In addition to laboratory testing and ultraviolet experiments, I developed a Python-based data tool that connects to a module database and allows selected testing conditions and module information to be retrieved and displayed efficiently. These different testing procedures, experimental processes, and computational tools support the broader goal of identifying module issues and improving modules that will be used in the CMS Outer Tracker Phase-2 Upgrade.

Siddiqui, Hooriya [DuPage Coll.; Fermilab] (ORCID:↗
DOE OSTI2026

A procedure for rule extraction from a Self-Organising plasma disruption predictor for JET

In a previous paper, a Self-Organizing Map had proven to be able to identify the regions of the plasma operative space characterizing the pre-disruptive phase at JET without relying on any a priori information. One of the strengths of this disruption predictor lies in its inherent self-organization capability. The Self-Organizing Map discovers non-trivial relationships and captures the complicated interplay of device diagnostics on the internal plasma states directly from the experimental data. Moreover, the provided model allows the visualization of high-dimensional plasma parameters and facilitates easy interrogation of the model to understand the reasons behind its correlations. In this paper, an additional step is taken towards the interpretability of models for predicting disruptions by training a Decision Tree to classify the plasma states according to the interpretation provided by the Self-Organizing Map (stable or at high risk of disruptions). The Decision tree provides a set of rules which describe the transition of the plasma towards the pre-disruptive phase as visualized in the Self-Organizing Map. The obtained rules for the database explored in the study identify four regions in the map, two of which are at risk of disruption. These regions correspond to partitions of a 3D space based on the peaking factors of the core and divertor radiation, as well as the Locked Mode. The agreement between the Self-Organizing Map answers and the rules supplied by the Decision Tree is confirmed by the comparison of the performance exhibited by the two models in the prediction of disruptions.

Setzu, Samuele [Univ. of Cagliari, Monserrato, Cag↗
DOE OSTI2018

An atomic-scale view of single-site Pt catalysis for low-temperature CO oxidation

Single-atom catalysts have attracted great attention in recent years due to their high efficiencies and cost savings. However, there is debate concerning the nature of the active site, interaction with the support, and mechanism by which single-atom catalysts operate. Here, using a combined surface science and theory approach, we designed a model system in which we unambiguously show that individual Pt atoms on a well-defined Cu 2 O film are able to perform CO oxidation at low temperatures. Isotopic labelling studies reveal that oxygen is supplied by the support. Density functional theory rationalizes the reaction mechanism and confirms X-ray photoelectron spectroscopy measurements of the neutral charge state of Pt. Scanning tunneling microscopy enables visualization of the active site as the reaction progresses, and infrared measurements of the CO stretch frequency are consistent with atomically dispersed Pt atoms. These results serve as a benchmark for characterizing, understanding and designing other single-atom catalysts.

Therrien, Andrew J.↗
DOE OSTI2023

Explainable Artificial Intelligence Technology for Predictive Maintenance

The domestic nuclear power plant fleet has relied on labor-intensive and time-consuming preventive maintenance programs, thus driving up operation and maintenance costs to achieve high-capacity factors. Artificial intelligence and machine learning can help simplify complex problems, such as diagnosing equipment degradation, to enable more effective decision-making. Benefits will be felt not only within existing analog and digital instrumentation and control, but also work processes, the integration of people with technology, and most importantly, the business case. Together, these hold promise to make nuclear power more efficient and reduce costs associated with operation and maintenance. While the artificial intelligence and machine learning technologies hold significant promise in the nuclear industry, there are challenges or barriers to their adoption. This report outlines the those different machine learning adoption barriers (categorized as historical, technical, economic, regulatory, and user) that the industry must overcome to realize the full benefits of artificial intelligence and machine learning capabilities for long-term economic sustainability. This report also provides solutions for some of these barriers by focusing on improving the explainability of machine learning to encourage trust from the end-user. Trust and explainability are essential to machine learning adoption. This report focuses on research-developed solutions to some of these barriers while analyzing a non-safety-related system, namely the circulating water system. This system frequently experiences waterbox fouling which our models preemptively diagnoses then explains to the operator how those conclusions were reached. This report presents and discusses the inherent trade-off between machine learning performance (in terms of accuracy) and explainability, where highly accurate machine learning methods (such as deep-learning) are the least explainable, and the most explainable methods (such as decision trees) are the least accurate. In addition, explainability of artificial intelligence techniques in terms of transparency and post-hoc metrics are discussed. This report outlines the importance of data novelty and value of new information in evaluating both the explainability and trustworthiness. Novelty detection helps to establish consistency or inconsistency of the new data with respect to the training data. On the other hand, value of information could be a part of the user-centric visualization recommendation system that request additional information to be collected, thereby strengthening the machine learning outcomes. During this project, a copyrighted user-centric visualization that aligns with a human-in-the-loop approach was developed. The user-centric visualization presents different levels of information and can be tailored as per user credentials to gain user confidence. One of the salient features of the user-centric visualization is it presents machine learning methods with explainability metrics. A simplified version of the user-centric visualization was presented to 32 users with varying levels of machine learning expertise. Feedback was solicited to test the hypothesis that the app contained sufficient explainability and that the users would trust the algorithm. Overall, the app was positively received, and the hypothesis was supported. This report discusses the trust-but-verify framework – a potential approach to build user trust artificial intelligence. The framework discusses trust from the human level to artificial intelligence level. The fundamental premise of the trust but verify framework is derived from an observation of nuclear safety culture (i.e., nuclear power plant personnel do not rely on a singular source of data to make a decision). This also ties back to the user-centric visualization that presents different levels of information to achieve both explainability and trustworthiness of artificial intelligence. Even so, the adoption of artificial intelligence and machine learning in the nuclear industry faces additional barriers, namely regulatory and stakeholder readiness. To overcome these challenges, new solutions must gain regulatory approval and cater to stakeholder needs. The Nuclear Regulatory Committee has a 5-year strategic plan which prepares them for reviewing artificial intelligence technologies in licensee submissions. Early and frequent engagement with the regulator is encouraged. Additionally, artificial intelligence solutions should incorporate human-in-the-loop considerations and offer explainability. Stakeholders must prepare by hiring or training staff to adapt to advancing technology in everyday plant tasks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2001

Two New Aircraft Traffic Surveillance Symbology Concepts: Range Filter and Inboard Field-of-View Symbology

The objective of this preliminary experiment was to investigate two head-up surveillance symbology (HUSS) display issues. The first issue was concerned with the benefits of adding a range filter to the current HUSS concept. A range filter limits the amount of traffic symbols displayed head-up by setting a range boundary (e.g., 7-nmi) around the ownship. The second issue was concerned with the need to incorporate HUSS in the inboard field-of-view (IFOV) display of the eXternal Visibility System (XVS) concept. The hypothesis tested was that adding a range filter to the XVS display and HUSS to the IFOV display would enhance the pilot's effectiveness in traffic surveillance tasks. Using a high-resolution graphics flight simulator, each of three pilots flew departure and arrival scenarios under visual meteorological conditions. The pilots' main tasks, while managing flight path, were to detect and assess potential airborne traffic hazards and to maintain overall situation awareness. Upon completing all the runs, each pilot completed a subjective questionnaire. Results showed that having both the HUSS on the IFOV and the range filter on each of the XVS displays enhanced the effectiveness of the XVS surveillance display concept. This configuration had the least head down time and the lowest mental workload. Combining both features gave the best target detection and, the earliest threat recognition performances, and enabled the pilots to create a better strategy for evasive action when it became necessary.

Wong, Douglas T.↗
NASA NTRS1998

Interaction of semicircular canal stimulation with carotid baroreceptor reflex control of heart rate

The carotid-cardiac baroreflex contributes to the prediction of orthostatic tolerance; experimental attenuation of the reflex response leads to orthostatic hypotension in humans and animals. Anecdotal observations indicate that rotational head movements about the vertical axis of the body can also induce orthostatic bradycardia and hypotension through increased parasympathetic activity. We therefore measured the chronotropic response to carotid baroreceptor stimulation in 12 men during varying conditions of vestibulo-oculomotor stimulation to test the hypothesis that stimulation of the semicircular canals associated with head movements in the yaw plane inhibits cardioacceleration through a vagally mediated baroreflex. Carotid-cardiac baroreflex response was assessed by plotting R-R intervals (ms) at each of 8 neck pressure steps with their respective carotid distending pressures (mmHg). Calculated baroreflex gain (maximal slope of the stimulus-response relationship) was measured under 4 experimental conditions: 1) sinusoidal whole-body yaw rotation of the subject in the dark without visual fixation (combined vestibular-oculomotor stimulation); 2) yaw oscillation of the subject while tracking a small head-fixed light moving with the subject (vestibular stimulation without eye movements); 3) subject stationary while fixating on a small light oscillating in yaw at the same frequency, peak acceleration, and velocity as the chair (eye movements without vestibular stimulation); and 4) subject stationary in the dark (no eye or head motion). Head motion alone and with eye movement reduced baseline baroreflex responsiveness to the same stimulus by 30%. Inhibition of cardioacceleration during rotational head movements may have significant impact on functional performance in aerospace environments, particularly in high-performance aircraft pilots during high angular acceleration in aerial combat maneuvers or in astronauts upon return from spaceflight who already have attenuated baroreflex functions.

Review, Tutorial↗
NASA NTRS2014

Wind Tunnel Testing of a 120th Scale Large Civil Tilt-Rotor Model in Airplane and Helicopter Modes

In April 2012 and October 2013, NASA and the U.S. Army jointly conducted a wind tunnel test program examining two notional large tilt rotor designs: NASA's Large Civil Tilt Rotor and the Army's High Efficiency Tilt Rotor. The approximately 6%-scale airframe models (unpowered) were tested without rotors in the U.S. Army 7- by 10-foot wind tunnel at NASA Ames Research Center. Measurements of all six forces and moments acting on the airframe were taken using the wind tunnel scale system. In addition to force and moment measurements, flow visualization using tufts, infrared thermography and oil flow were used to identify flow trajectories, boundary layer transition and areas of flow separation. The purpose of this test was to collect data for the validation of computational fluid dynamics tools, for the development of flight dynamics simulation models, and to validate performance predictions made during conceptual design. This paper focuses on the results for the Large Civil Tilt Rotor model in an airplane mode configuration up to 200 knots of wind tunnel speed. Results are presented with the full airframe model with various wing tip and nacelle configurations, and for a wing-only case also with various wing tip and nacelle configurations. Key results show that the addition of a wing extension outboard of the nacelles produces a significant increase in the lift-to-drag ratio, and interestingly decreases the drag compared to the case where the wing extension is not present. The drag decrease is likely due to complex aerodynamic interactions between the nacelle and wing extension that results in a significant drag benefit.

Wind Tunnel Testing of a 1/20th Scale↗
NASA NTRS2016

Validation for Global Solar Wind Prediction Using Ulysses Comparison: Multiple Coronal and Heliospheric Models Installed at the Community Coordinated Modeling Center

The prediction of the background global solar wind is a necessary part of space weather forecasting. Several coronal and heliospheric models have been installed and/or recently upgraded at the Community Coordinated Modeling Center (CCMC), including the Wang-Sheely-Arge (WSA)-Enlil model, MHD-Around-a-Sphere (MAS)-Enlil model, Space Weather Modeling Framework (SWMF), and Heliospheric tomography using interplanetary scintillation data. Ulysses recorded the last fast latitudinal scan from southern to northern poles in 2007. By comparing the modeling results with Ulysses observations over seven Carrington rotations, we have extended our third-party validation from the previous near-Earth solar wind to middle to high latitudes, in the same late declining phase of solar cycle 23. Besides visual comparison, wehave quantitatively assessed the models capabilities in reproducing the time series, statistics, and latitudinal variations of solar wind parameters for a specific range of model parameter settings, inputs, and grid configurations available at CCMC. The WSA-Enlil model results vary with three different magnetogram inputs.The MAS-Enlil model captures the solar wind parameters well, despite its underestimation of the speed at middle to high latitudes. The new version of SWMF misses many solar wind variations probably because it uses lower grid resolution than other models. The interplanetary scintillation-tomography cannot capture the latitudinal variations of solar wind well yet. Because the model performance varies with parameter settings which are optimized for different epochs or flow states, the performance metric study provided here can serve as a template that researchers can use to validate the models for the time periods and conditions of interest to them.

Jian, L. K.↗
NASA NTRS1984

Development of an advanced pitch active control system for a wide body jet aircraft

An advanced PACS control law was developed for a commercial wide-body transport (Lockheed L-1011) by using modern control theory. Validity of the control law was demonstrated by piloted flight simulation tests on the NASA Langley visual motion simulator. The PACS design objective was to develop a PACS that would provide good flying qualities to negative 10 percent static stability margins that were equivalent to those of the baseline aircraft at a 15 percent static stability margin which is normal for the L-1011. Also, the PACS was to compensate for high-Mach/high-g instabilities that degrade flying qualities during upset recoveries and maneuvers. The piloted flight simulation tests showed that the PACS met the design objectives. The simulation demonstrated good flying qualities to negative 20 percent static stability margins for hold, cruise and high-speed flight conditions. Analysis and wind tunnel tests performed on other Lockheed programs indicate that the PACS could be used on an advanced transport configuration to provide a 4 percent fuel savings which results from reduced trim drag by flying at negative static stability margins.

Guinn, Wiley A.↗
NASA NTRS1986

Visual and motion cueing in helicopter simulation

The visual cues presented in the simulator are compared with those of flight in an attempt to identify deficiencies. For the low-amplitude maneuvering tasks normally associated with the hover mode, the unique motion capabilities of the Vertical Motion Simulator (VMS) at Ames Research Center permit nearly a full representation of vehicle motion. Especially appreciated in these tasks are the vertical-acceleration responses to collective control. For larger-amplitude maneuvering, motion fidelity must suffer diminution through direct attenuation through high-pass filtering washout of the computer cockpit accelerations or both. Experiments were conducted in an attempt to determine the effects of these distortions on pilot performance of height-control tasks.

Bray, Richard S.↗
NASA NTRS1988

Transport delay compensation for computer-generated imagery systems

In the problem of pure transport delay in a low-pass system, a trade-off exists with respect to performance within and beyond a frequency bandwidth. When activity beyond the band is attenuated because of other considerations, this trade-off may be used to improve the performance within the band. Specifically, transport delay in computer-generated imagery systems is reduced to a manageable problem by recognizing frequency limits in vehicle activity and manual-control capacity. Based on these limits, a compensation algorithm has been developed for use in aircraft simulation at NASA Ames Research Center. For direct measurement of transport delays, a beam-splitter experiment is presented that accounts for the complete flight simulation environment. Values determined by this experiment are appropriate for use in the compensation algorithm. The algorithm extends the bandwidth of high-frequency flight simulation to well beyond that of normal pilot inputs. Within this bandwidth, the visual scene presentation manifests negligible gain distortion and phase lag. After a year of utilization, two minor exceptions to universal simulation applicability have been identified and subsequently resolved.

Mcfarland, Richard E.↗