Results for “Analytics” — Page 34

NASA NTRS2021

Analytical Methods and Testbeds for Characterizing Adsorbents and Catalysts for Atmosphere Revitalization of Crewed Spacecraft

Spacecraft environmental control and life support systems (ECLSS) include a number of air revitalization (AR) technologies to provide breathable air and a comfortable living environment to the crew. Crew health and comfort is ensured by controlling human produced CO2 (1 kg person-1 day-1) and water vapor (~2 kg person-1 day-1), and by removing trace contaminants (TCs) from cabin air. These life support functions on-board the International Space Station (ISS) are carried out by the Carbon Dioxide Removal Assembly (CDRA), the Water Processor Assembly (WPA), and the trace contaminant control system (TCCS). During the development of the TCCS, new analytical and theoretical methods were developed in the 1970s for characterizing adsorption and desorption characteristics of activated carbons for the purpose of designing suitable AR technologies required for controlling airborne trace contaminants within spacecraft cabins during long exploration missions. The TCCS removes harmful volatile organic compounds and other trace contaminants from the circulating air. It consists of a granular activated carbon (GAC) bed for the removal of high molecular weight contaminants and ammonia followed by a heated catalytic bed for low molecular weight hydrocarbons. The high temperature catalytic oxidizer (HTCO) of the TCCS, which operates at 400°C and requires 120W average power, removes low molecular weight compounds such as carbon monoxide (CO), formaldehyde (CH2O), and methane (CH4), that pass through the GAC bed. The Air Revitalization Laboratory at the Kennedy Space Center (KSC) was established to develop new analytical methods for evaluating emerging ECLSS technologies for use in future AR architectures. General properties of adsorbents and catalysts are required for trace contaminant control system design calculations and vendor-supplied data are seldom available at relevant process conditions of interest to spacecraft cabin applications. To address this shortcoming, appropriate testbeds were developed to measure the desired properties of AR technologies being considered for use in ECLS architectures. Generally, the testbeds developed at KSC challenge the test media (activated carbon, impregnated activated carbon, catalysts, zeolites, solid amines, or pleated filters) with simulated spacecraft gas streams containing representative mixtures of trace contaminants (volatile organic compounds, ammonia, CO, CO2, or siloxanes) at the flow rates, temperatures, and relative humidity that will be encountered within manned spacecraft. Work performed at KSC funded by NASA’s Advanced Exploration (AES) Program has included: Identifying candidate sorbents to replace commercially obsolete impregnated carbons for NH3 control within the TCCS, characterizing their adsorptive capacities using simulated spacecraft gas streams, and ranking their appropriateness in various AR applications; evaluating novel low temperature catalysts for controlling CO and formaldehyde by traditional and photocatalytic methods for trace contaminant control; development of analytical methods to assess regenerable solid amine performance for CO2 control via pressure swing adsorption. The Air Revitalization lab was also funded to study trace contaminant control by other NASA programs. These include: screening of candidate sorbents for the design of new Charcoal HEPA Integrated Particle Scrubber (CHIPS) filters for removing siloxanes from cabin air; characterizing the performance of an impregnated activated carbon at low humidity for use in ORION ECLS; screening of sorbents for protecting the Sabatier 2.0 catalyst from DMSO2, siloxanes, NH3, and solid amine byproducts.

Monje, Oscar↗

NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗

NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗

NASA NTRSDate not supplied

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

The purpose of this paper is to extend previously demonstrated methodologies for design under uncertainty, leveraging analytical gradients to higher fidelity analysis for use in conceptual aircraft design. Previous work developed methods to generate analytical derivatives through polynomial chaos expansion, eliminating the need to estimate derivatives via complex step or finite difference. In this research, the authors build upon the methods to include physics-based aircraft design codes for aircraft design under uncertainty. This extends the previous work’s case study, which employed analytical aerodynamics and Breguet range estimations for wing design, to a higher fidelity level. In addition, this work extends previous work on interface development between the Uncertainty Quantification with Polynomial Chaos Expansion (UQPCE) software and Model-Based Systems Analysis and Engineering (MBSA&E) frameworks. This paper will discuss the development work necessary to perform multidisciplinary design under uncertainty as well as demonstrate the mechanics of interfacing UQPCE and conceptual aircraft design tools such as NASA’s Aviary code. In a case study, a conceptual aircraft design under uncertainty was conducted and compared against a traditional deterministic design. When given information about the uncertainty space from UQPCE, the optimizer was able to shape the output distribution and produce a more robust design

UQ↗

NASA NTRSDate not supplied

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

The purpose of this paper is to extend previously demonstrated methodologies for design under uncertainty, leveraging analytical gradients to higher fidelity analysis for use in conceptual aircraft design. Previous work developed methods to generate analytical derivatives through polynomial chaos expansion, eliminating the need to estimate derivatives via complex step or finite difference. In this research, the authors build upon the methods to include physics-based aircraft design codes for aircraft design under uncertainty. This extends the previous work’s case study, which employed analytical aerodynamics and Breguet range estimations for wing design, to a higher fidelity level. In addition, this work extends previous work on interface development between the Uncertainty Quantification with Polynomial Chaos Expansion (UQPCE) software and Model-Based Systems Analysis and Engineering (MBSA&E) frameworks. This paper will discuss the development work necessary to perform multidisciplinary design under uncertainty as well as demonstrate the mechanics of interfacing UQPCE and conceptual aircraft design tools such as NASA’s Aviary code. In a case study, a conceptual aircraft design under uncertainty was conducted and compared against a traditional deterministic design. When given information about the uncertainty space from UQPCE, the optimizer was able to shape the output distribution and produce a more robust design.

UQ↗

DOE OSTI2013

Performance implications from sizing a VM on multi-core systems: A Data analytic application s view

In this paper, we present a quantitative performance analysis of data analytics applications running on multi-core virtual machines. Such environments form the core of cloud computing. In addition, data analytics applications, such as Cassandra and Hadoop, are becoming increasingly popular on cloud computing platforms. This convergence necessitates a better understanding of the performance and cost implications of such hybrid systems. For example, the very rst step in hosting applications in virtualized environments, requires the user to con gure the number of virtual processors and the size of memory. To understand performance implications of this step, we benchmarked three Yahoo Cloud Serving Benchmark (YCSB) workloads in a virtualized multi-core environment. Our measurements indicate that the performance of Cassandra for YCSB workloads does not heavily depend on the processing capacity of a system, while the size of the data set is critical to performance relative to allocated memory. We also identi ed a strong relationship between the running time of workloads and various hardware events (last level cache loads, misses, and CPU migrations). From this analysis, we provide several suggestions to improve the performance of data analytics applications running on cloud computing environments.

Lim, Seung-Hwan↗

DOE OSTI2013

Oak Ridge Bio-surveillance Toolkit (ORBiT): Integrating Big-Data Analytics with Visual Analysis for Public Health Dynamics

In this position paper, we describe the design and implementation of the Oak Ridge Bio-surveillance Toolkit (ORBiT): a collection of novel statistical and machine learning tools implemented for (1) integrating heterogeneous traditional (e.g. emergency room visits, prescription sales data, etc.) and non-traditional (social media such as Twitter and Instagram) data sources, (2) analyzing large-scale datasets and (3) presenting the results from the analytics as a visual interface for the end-user to interact and provide feedback. We present examples of how ORBiT can be used to summarize ex- tremely large-scale datasets effectively and how user interactions can translate into the data analytics process for bio-surveillance. We also present a strategy to estimate parameters relevant to dis- ease spread models from near real time data feeds and show how these estimates can be integrated with disease spread models for large-scale populations. We conclude with a perspective on how integrating data and visual analytics could lead to better forecasting and prediction of disease spread as well as improved awareness of disease susceptible regions.

Ramanathan, Arvind↗

DOE OSTI2015

Trace detection of analytes using portable raman systems

Apparatuses and methods for in situ detection of a trace amount of an analyte are disclosed herein. In a general embodiment, the present disclosure provides a surface-enhanced Raman spectroscopy (SERS) insert including a passageway therethrough, where the passageway has a SERS surface positioned therein. The SERS surface is configured to adsorb molecules of an analyte of interest. A concentrated sample is caused to flow over the SERS surface. The SERS insert is then provided to a portable Raman spectroscopy system, where it is analyzed for the analyte of interest.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Analytical Methods for Biomass Characterization during Pretreatment and Bioconversion

Lignocellulosic biomass has been introduced as a promising resource for alternative fuels and chemicals because of its abundance and complement for petroleum resources. Biomass is a complex biopolymer and its compositional and structural characteristics largely vary depending on its species as well as growth environments. Because of complexity and variety of biomass, understanding its physicochemical characteristics is a key for effective biomass utilization. Characterization of biomass does not only provide critical information of biomass during pretreatment and bioconversion, but also give valuable insights on how to utilize the biomass. For better understanding biomass characteristics, good grasp and proper selection of analytical methods are necessary. This chapter introduces existing analytical approaches that are widely employed for biomass characterization during biomass pretreatment and conversion process. Diverse analytical methods using Fourier transform infrared (FTIR) spectroscopy, gel permeation chromatography (GPC), and nuclear magnetic resonance (NMR) spectroscopy for biomass characterization are reviewed. In addition, biomass accessibility methods by analyzing surface properties of biomass are also summarized in this chapter.

accessibility↗

DOE OSTI2017

Semi-Analytical Benchmarks for MCNP6 [Slides]

This presentation begins with an Introduction and some background on semi-analytical benchmarks for MCNP6. Discussion topics include: verification & validation, MCNP history of V&V, semi-analytic benchmarks, numerical Results, comparison of semi-analytic to MCNP, and tips for proper comparison. This presentation ends with conclusions & future Work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

On Concavity and Utilization Analytics of Wide-Area Network Transport Protocols

Wide-area data transfers in high-performance computing infrastructures and big data applications are increasingly carried over dynamically provisioned dedicated network connections, which provide high capacities with no competing traffic. Throughput of TCP and UDT over wide-area connections depends, often in a complex non-linear way, on the congestion control mechanism, buffer sizes, and the number of parallel streams. In addition, our extensive TCP and UDT throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs) show significant statistical and temporal variations. Consequently, parameter selection and optimization for transport methods require data analytics to complement analytical throughput models. We present analytics based on the concavity-convexity of throughput profiles which provide insights into peak throughput and superior/inferior trend compared to linear interpolations based on RTT. In particular, we propose the utilization-concavity coefficient, a scalar metric that incorporates both utilization and concavity profile to characterize the overall performance of a transport protocol. These measurements-based anaytics enable us to select a transport protocol and its parameters for a given host and connection configuration to achieve high throughput with statistical guarantees.

Rao, Nageswara↗

DOE OSTI2018

When Data Analytics Meet Site Operation: Benefits and Challenges

Demand for using data analytics for energy management in buildings is rising. Such analytics are required for advanced measurement and verification, commissioning, automated fault-detection and diagnosis, and optimal control. While novel analytics algorithms continue to be developed, bottlenecks and challenges arise when deploying them for demonstration, for a number of reasons that do not necessarily have to do with the algorithms themselves. It is important for developers of new technologies to be aware of the challenges and potential solutions during demonstration. Therefore, this paper describes a recent deployment of an automated, physical model-based, FDD and optimal control tool, highlighting its design and as-operated benefits that the tool provides. Furthermore, the paper presents challenges faced during deployment and testing along with solutions used to overcome these challenges. The challenges have been grouped into four categories: Data Management, Physical Model Development and Integration, Software Development and Deployment, and Operator Use. The paper concludes by discussing how challenges with this project generalize to common cases, how they could compare to other projects in their severity, and how they may be addressed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Rapid and continuous analyte processing in droplet microfluidic devices

The compositions and methods described herein are designed to introduce functionalized microparticles into droplets that can be manipulated in microfluidic devices by fields, including electric (dielectrophoretic) or magnetic fields, and extracted by splitting a droplet to separate the portion of the droplet that contains the majority of the microparticles from the part that is largely devoid of the microparticles. Within the device, channels are variously configured at Y- or T junctions that facilitate continuous, serial isolation and dilution of analytes in solution. The devices can be limited in the sense that they can be designed to output purified analytes that are then further analyzed in separate machines or they can include additional channels through which purified analytes can be further processed and analyzed.

Strey, Helmut↗

DOE OSTI2020

Device and system for selective ionization and analyte detection and method of using the same

Disclosed herein are embodiments of a system for selectively ionizing samples that may comprise a plurality of different analytes that are not normally detectable using the same ionization technique. The disclosed system comprises a unique split flow tube that can be coupled with a plurality of ionization sources to facilitate using different ionization techniques for the same sample. Also disclosed herein are embodiments of a method for determining the presence of analytes in a sample, wherein the number and type of detectable analytes that can be identified is increased and sensitivity and selectivity are not sacrificed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2021

Device and system for selective ionization and analyte detection and method of using the same

Disclosed herein are embodiments of a system for selectively ionizing samples that may comprise a plurality of different analytes that are not normally detectable using the same ionization technique. The disclosed system comprises a unique split flow tube that can be coupled with a plurality of ionization sources to facilitate using different ionization techniques for the same sample. Also disclosed herein are embodiments of a method for determining the presence of analytes in a sample, wherein the number and type of detectable analytes that can be identified is increased and sensitivity and selectivity are not sacrificed.

Denis, Elizabeth↗

DOE OSTI2023

Operational Focused Data Analytics for Optimizing Radiation Portal Monitor-Based Nuclear Smuggling Detection Systems at Global Ports of Entry

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence has deployed a fleet of radiation portal monitors (RPMs) across the world at global ports of entry including seaports, airports, and land border crossings. These RPMs are integrated into radiation detection systems (RDS) that also include fixed cameras, optical character recognition (OCR) systems, primary scanning systems (e.g., X-ray or gamma-ray), and secondary scanning systems (e.g., spectroscopic radiation portal monitors, portable radiation detection systems). The data from these sensing technologies is collected at the Central Alarm Station (CAS) where servers and computers reside to control and operate the system. Operators utilize the data collected by the CAS and declared cargo information to make decisions on how to respond to an alarm.This work explores the use of CAS-located data, looking at both the sensor data streams and operator inputs, to perform analysis which supports customs and border protection agencies to improve training capability and operational effectiveness. We focus on analyzing site level effectiveness and behavior by rolling up CAS-located data collected from individual occurrences. To-date, more than 15 sites (e.g., seaports, airports, border crossings) have been analyzed in this manner with the goal of understanding system operations to verify effectiveness and recommend potential improvements. This work first aims to provide background information on relevant CAS-located data sources and our current operational system analytics process including example results. After summarizing our current analytic techniques, we discuss how the future data analytics systems can provide key benefits to improving operational performance while minimizing the burden these detection systems place on operators.

Kuhn, Michael↗

DOE OSTI2019

Analytical Approach to Evaluate Uncertainty in Discharged Inventory Estimates at the Hanford Site - 19012

Many waste sites (>400) located within the Central Plateau portion of the Hanford Site received liquid discharges during the nuclear weapons material production mission (1944-1988). The Hanford Soil Inventory Model (SIM) is developed to quantitatively evaluate the discharged inventory for important radionuclides and chemicals at a given waste site to support fate and transport modeling of contaminants. An analytic approach was developed to estimate inventory and associated uncertainty. The approach was implemented for SIM and compared to a prior stochastic implementation applying a Monte-Carlo sampling approach. The analytic approach provides exact mean and variance results and the run times are much faster compared to the Monte-Carlo sampling approach. With the improved solution method using the analytical approach, it is feasible to run inventory updates and reduce associated uncertainty ranges. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Proposed Analytical Methods for Determining Filter Media Properties

High Efficiency Particulate Air (HEPA) filters, commonly used in nuclear filtration applications, are an integral part of the waste management processes in nuclear plants. HEPA filters are 99.97% efficient filtration devices characterized by their high resistance to air flow, or pressure drop. From theoretical models, the initial pressure drop across a clean filter is proven to be a function of the filter media fiber diameters and porosity of the media. These filter properties are relatively difficult to obtain with traditional manual methods; therefore, there is a need to develop analytical methods to find the fiber diameter and porosity to determine the pressure drop. Typically, these values can be found by substituting a calculated representative value based upon measured values, such as equivalent fiber diameter based upon a clean pressure drop. However, these values may also be directly recorded and measured by incorporating Scanning Electron Microscope (SEM) image analysis and other measurement methods to analyze the filter media and determine its physical properties without the need for media testing. DiameterJ, an open source Java plug-in, used with ImageJ, can process images of filter media taken by an SEM to find statistical data such as mean fiber diameter and porosity. To produce the raw data, SEM images of two filter media type samples are taken and segmented in DiameterJ using the traditional and statistical region merging segmentation algorithms. Manual segmentation is necessary after the initial segmentation by the algorithms as the images tend to be too complex for the algorithms to output with the necessary accuracy. However, complications exist in the manual segmentation process as these methods can be time intensive and prone to the individual bias of the user. This in turn can skew the final mean fiber diameter result, and lead to either an over or under prediction of the pressure drop. It was also discovered that the porosity data produced by DiameterJ is inaccurate, as the SEM analyzes the three-dimensional filter media by projecting its geometry onto a plane and analyzing it as a two-dimensional binary image. Thus, the porosity is artificially inflated through the segmentation process, rendering this result incorrect. Alternatively, density determination, gravimetric analysis, and thickness testing of the filter media is collectively used to determine the filter fiber porosity. Together, the SEM image analysis and analytical lab methods produce results through direct measurements which allow for the prediction of the initial pressure drop from clean filter media without the need for prior media testing to collect pressure data. By improving upon this proposed analytical method in the future, there is potential to streamline the process of finding these filter properties into a more direct methodology for determining the pressure drop across HEPA filters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗