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COLUTA: Custom 8-Channel 15-bit 40-MSPS ADC for the ATLAS Liquid Argon Calorimeter Readout
The stringent radiation-tolerance, quantization requirements, and the need for seamless integration of the on-detector readout electronics chain require the design of a full-custom analog-to-digital converter (ADC) for the 182,468 channels in the ATLAS Liquid Argon (LAr) calorimeter at the Large Hadron Collider (LHC) at CERN, as part of the High-Luminosity LHC (HL-LHC) upgrade. Each of the 8 channels in the prototype 65 nm CMOS ADC with 15-bit resolution and >68 dB signal-to-noise-and-distortion ratio (SNDR), or equivalently >11 effective number of bits (ENOB), consists of a Multiplying-DAC (MDAC) and a successive-approximation (SAR) ADC. A digital data processing unit (DDPU) calibrates and serially transmits the quantized data. Initial lab characterization of 18 chips shows a minimum SNDR of 69.5 dB at full-scale at about 5 MHz and a maximum power consumption of 1.17 W; differential non-linearity (DNL) measurements show no missing codes. Additional validation of the ADC is ongoing before approximately 70k chips can be mass-produced for the upgrade.
BOREAS TE-8 Aspen Bark Spectral Reflectance Data
The BOREAS TE-08 team collected in-lab spectral reflectance data for aspen bark and leaves from three sites within the BOREAS SSA from 24-May-1994 to 16-Jun-1994 (IFC 1), 19-Jul-1994 to 08-Aug-1994 (IFC 2), and 30-Aug-1994 to 19-Sep-1994 (IFC 3). One to nine trees from each site were sampled during the three IFCs. Each tree was sampled in five different locations for bark spectral properties: BS, US, BR, BT, and BO. Additionally, a limited number of LV were collected. Bark samples were removed from the stem of the tree and placed in ziplock bags for transport to UNH, where they were scanned with a spectroradiometer in a controlled environment. Each sample was scanned twice: the first set of measurements was made with the bark surface moistened, and the second set was made with the bark surface air-dried for a period of 30 minutes. These data represent continuous spectra of bark reflectance. Each sample was scanned three times, rotating the sample when possible. The reported values for each sample are an average over the three scans. The data are provided in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
Integrated Data Visualization for Human Missions
Interplanetary missions produce exceptionally large and complex volumes of data that can be extremely difficult to navigate. This is especially true for human missions. This project seeks to develop an integrated data visualization environment that builds on the success of Apollo17.org allowing for integration of operational, engineering and scientific data while also preserving the context under which it was collected during the mission. We will build a product that integrates existing data from the Neutral Buoyancy Lab (NBL) to improve data visualization for extra vehicular activity and interplanetary missions.
Visible and Near-IR Reflectance Spectra of Smectite Acquired Under Dry Conditions for Interpretation of Martian Surface Mineralogy
Visible and near-IR (VNIR) spectra from the MEx OMEGA and the MRO CRISM hyper-spectral imaging instruments have spectral features associated with the H2O molecule and M OH functional groups (M = Mg, Fe, Al, and Si). Mineralogical assignments of martian spectral features are made on the basis of laboratory VNIR spectra, which were often acquired under ambient (humid) conditions. Smectites like nontronite, saponite, and montmorillionite have interlayer H2O that is exchangeable with their environment, and we have acquired smectite reflectance spectra under dry environmental conditions for interpretation of martian surface mineralogy. We also obtained chemical, Moessbauer (MB), powder X-ray diffraction (XRD), and thermogravimetric (TG) data to understand variations in spectral properties. VNIR spectra were recorded in humid lab air at 25-35C, in a dynamic dry N2 atmosphere (50-150 ppmv H2O) after exposing the smectite samples (5 nontronites, 3 montmorillionites, and 1 saponite) to that atmosphere for up to approximately l000 hr each at 25-35C, approximately 105C, and approximately 215C, and after re-exposure to humid lab air. Heating at 105C and 215C for approximately 1000 hr is taken as a surrogate for geologic time scales at lower temperatures. Upon exposure to dry N2, the position and intensity of spectral features associated with M-OH were relatively insensitive to the dry environment, and the spectral features associated with H2O (e.g., approximately 1.90 micrometers) decreased in intensity and are sometimes not detectable by the end of the 215C heating step. The position and intensity of H2O spectral features recovered upon re-exposure to lab air. XRD data show interlayer collapse for the nontronites and Namontmorillionites, with the interlayer remaining collapsed for the latter after re-exposure to lab air. The interlayer did not collapse for the saponite and Ca-montmorillionite. TG data show that the concentration of H2O derived from structural OH was invariant to the dry N2 treatment for saponite and the montmorillionites, but the nontronites had additional structural OH after treatment. Upon exposure to dry N2, the VNIR spectra also acquired a red slope with decreasing albedo between approximately 0.4 and approximately 2.0 micrometers. The magnitude of the effects covaries with exposure time to dry N2 and heating temperature. Upon re-exposure to lab air, the slope and albedo do not completely recover to pre-exposure values. MB data show that these effects do not result from partial reduction of ferric to ferrous iron, and TG data show they do not result from loss of structural OH. Possible explanations include formation of small clusters of (superparamagnetic) ferric oxide and reduced smectite crystallinity. The difference in spectral properties between spectra acquired in humid lab air and under dry conditions are consequential for interpretation of CRISM and OMEGA spectra. For example, nontronite by itself and not nontronite plus ferrihydrite can account for the red spectral slope in martian spectra where nontronite is indicated by the Fe-OH spectral features.
Data Acquisition in Space: Jet Propulsion Lab Relies on Macintosh Technology for Critical Testing
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The Importance of Data Visualization: Incorporating Storytelling into the Scientific Presentation
From its inception in 2000, one of the primary tasks of the Biomedical Data Reduction Analysis (BDRA) group has been translation of large amounts of data into information that is relevant to the audience receiving it. BDRA helps translate data into an integrated model that supports both operational and research activities. This data integrated model and subsequent visual data presentations have contributed to BDRA's success in delivering the message (i.e., the story) that its customers have needed to communicate. This success has led to additional collaborations among groups that had previously not felt they had much in common until they worked together to develop solutions in an integrated fashion. As more emphasis is placed on working with "big data" and on showing how NASA's efforts contribute to the greater good of the American people and of the world, it becomes imperative to visualize the story of our data to communicate the greater message we need to share. METHODS To create and expand its data integrated model, BDRA has incorporated data from many different collaborating partner labs and other sources. Data are compiled from the repositories of the Lifetime Surveillance of Astronaut Health and the Life Sciences Data Archive, and from the individual laboratories at Johnson Space Center that support collection of data from medical testing, environmental monitoring, and countermeasures, as designated in the Medical Requirements Integration Documents. Ongoing communication with the participating collaborators is maintained to ensure that the message and story of the data are retained as data are translated into information and visual data presentations are delivered in different venues and to different audiences. RESULTS We will describe the importance of storytelling through an integrated model and of subsequent data visualizations in today's scientific presentations and discuss the collaborative methods used. We will illustrate the discussion with examples of graphs from BDRA's past work supporting operations and/or research efforts.
Improving Efficiency & Quality of Data Acquisition in the Environmental Test Lab
No abstract available
Performance Risk Model Validation with Operationally Relevant Tasks
Human Research Program aims to develop methods to support astronauts’ health and productivity during spaceflight. The Crew Health and Performance Probabilistic Risk Assessment (CHP-PRA) team uses powerful computational methods to predict mission risk in both domains: medical and performance. Here, we show how CHP-PRA uses the Performance Risk Model (PRisM) to quantify the performance risk and show an application of the model on operationally relevant tasks. There are various metrics adopted across performance researchers that PRisM can accommodate. For data analysis, interpretation, and integration, we use a method of unifying data from multiple sources by converting each to a single metric. We consult subject matter experts prior to integrating the converted data into PRisM. The method we use is inspired by the Cooper-Harper rating scale [1]. Using this unified metric, we can easily combine data from various tests and lab groups. We explain our conversion method in detail and show how it pertains to the process of testing and validation of PRisM on operational tasks. We conducted an initial validation in collaboration with the Behavioral Health and Performance (BHP) lab. We test PRisM using data on their operationally relevant task ROBoT-r, a track-and-capture task for grappling incoming resupply vehicles [2]. Several other labs at NASA Johnson Space Center worked together to design 7 Functional Task Tests (FTTs) in pursuit of simulating the tasks required after landing on a planetary surface and after return to Earth [3]. Here we use the results from both ROBoT-r and the 7 FTTs and compare their experiment data to PRisM’s computational output to demonstrate how PRisM can support operations by predicting crew performance on future missions.
Experimental characterization of the effects of pneumatic tubing on unsteady pressure measurements
Advances in aircraft control system designs have, with increasing frequency, required that air data be used as flight control feedback. This condition requires that these data be measured with accuracy and high fidelity. Most air data information is provided by pneumatic pressure measuring sensors. Typically unsteady pressure data provided by pneumatic sensing systems are distorted at high frequencies. The distortion is a result of the pressure being transmitted to the pressure sensor through a length of connective tubing. The pressure is distorted by frictional damping and wave reflection. As a result, air data provided all-flush, pneumatically sensed air data systems may not meet the frequency response requirements necessary for flight control augmentation. Both lab and flight test were performed at NASA-Ames to investigate the effects of this high frequency distortion in remotely located pressure measurement systems. Good qualitative agreement between lab and flight data are demonstrated. Results from these tests are used to describe the effects of pneumatic distortion in terms of a simple parametric model.
Numerical modeling studies of wake vortex transport and evolution within the planetary boundary layer
The proposed research involves four tasks. The first of these is to simulate accurately the turbulent processes in the atmospheric boundary layer. TASS was originally developed to study meso-gamma scale phenomena, such as tornadic storms, microbursts and windshear effects in terminal areas. Simulation of wake vortex evolution, however, will rely on appropriate representation of the physical processes in the surface layer and mixed layer. This involves two parts. First, a specified heat flux boundary condition must be implemented at the surface. Using this boundary condition, simulation results will be compared to experimental data and to other model results for validation. At this point, any necessary changes to the model will be implemented. Next, a surface energy budget parameterization will be added to the model. This will enable calculation of the surface fluxes by accounting for the radiative heat transfer to and from the ground and heat loss to the soil rather than simple specification of the fluxes. The second task involves running TASS with prescribed wake vortices in the initial condition. The vortex models will be supplied by NASA Langley Research Center. Sensitivity tests will be performed on different meteorological environments in the atmospheric boundary layer, which include stable, neutral, and unstable stratifications, calm and severe wind conditions, and dry and wet conditions. Vortex strength may be varied as well. Relevant non-dimensional parameters will include the following: Richardson number or Froude number, Bowen ratio, and height to length scale ratios. The model output will be analyzed and visualized to better understand the transport, decay, and growth rates of the wake vortices. The third task involves running simulations using observed data. MIT Lincoln Labs is currently planning field experiments at the Memphis airport to measure both meteorological conditions and wake vortex characteristics. Once this data becomes available, it can be used to validate the model for vortex behavior under different atmospheric conditions. The fourth task will be to simulate the wake in a more realistic environment covering a wider area. This will involve grid nesting, since high resolution will be required in the wake region but a larger total domain will be used. During the first allocation year, most of the first task will be accomplished.
Laboratory Studies of Astronomical Ices: Reaction Chemistry and Spectroscopy
In this article, we will describe the work of the Cosmic Ice Laboratory at NASA’s Goddard Space Flight Center to characterize the composition of and to understand the chemistry occurring in icy bodies in the Solar System and beyond. Our work has touched on a wide range of extraterrestrial environments including icy interstellar grains, small bodies such as comets and asteroids, and planets and moons. We are especially interested in the chemical and physical changes that occur in ices as a result of thermal changes or exposure to radiation. To this end, we conduct experiments designed to simulate cold extraterrestrial environments and measure physical properties of single- and multi-component ices. We expose ices to radiation (e.g., MeV protons or keV-MeV electrons) or high-energy photons (e.g., UV) to initiate physical and chemical changes. We conduct experiments using cryo-vacuum chambers equipped with analytical tools and radiation sources to make most of our measurements, including the collection of all spectroscopic data,in situ. When possible and appropriate, we also collect reaction products for further ex situ analysis. The work of the Cosmic Ice Lab provides critical data to astrochemists and others seeking to understand observations, make predictions, and plan future space missions.
BOREAS TGB-1/TGB-3 CH4 Chamber Flux Data over the NSA Fen
The BOREAS TGB-3 team collected methane (CH4) chamber flux measurements at the NSA fen site during May-September 1994 and June-October 1996. Gas samples were extracted approximately every 7 days from chambers and analyzed at the NSA lab facility. The data are provided in tabular ASCII files.
BOREAS TGB-1/TGB-3 NEE Data over the NSA Fen
The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB-1) and TGB-3 teams collected several data sets that contributed to understanding the measured trace gas fluxes over sites in the Northern Study Area (NSA). This data set contains Net Ecosystem Exchange of CO2 (NEE) measurements collected with chambers at the NSA fen in 1994 and 1996. Gas samples were extracted approximately every 7 days from chambers and analyzed at the NSA lab facility. The data are provided in tabular ASCII files.
BOREAS TGB-1 NSA CH4 and CO2 Chamber Flux Data
The BOREAS TGB-1 team made methane (CH4) and carbon dioxide (CO2) dark chamber flux measurements at the NSA-OJP, NSA-OBS, NSA-BP, and NSA-YJP sites from 16-May-1994 through 13-Sep-1994. Gas samples were extracted approximately every 7 days from dark chambers and analyzed at the NSA lab facility. The data are provided in tabular ASCII files.
Metrology - Beyond the Calibration Lab
We rely on data from measurements every day; a gas-pump, a speedometer, and a supermarket weight scale are just three examples of measurements we use to make decisions. We generally accept the data from these measurements as "valid." One reason we can accept the data is the "legal metrology" requirements established and regulated by the government in matters of commerce. The measurement data used by NASA, other government agencies, and industry can be critical to decisions which affect everything from economic viability, to mission success, to the security of the nation. Measurement data can even affect life and death decisions. Metrology requirements must adequately provide for risks associated with these decisions. To do this, metrology must be integrated into all aspects of an industry including research, design, testing, and product acceptance. Metrology, the science of measurement, has traditionally focused on the calibration of instruments, and although instrument calibration is vital, it is only a part of the process that assures quality in measurement data. For example, measurements made in research can influence the fundamental premises that establish the design parameters, which then flow down to the manufacturing processes, and eventually impact the final product. Because a breakdown can occur anywhere within this cycle, measurement quality assurance has to be integrated into every part of the life-cycle process starting with the basic research and ending with the final product inspection process. The purpose of this paper is to discuss the role of metrology in the various phases of a product's life-cycle. For simplicity, the cycle will be divided in four broad phases, with discussions centering on metrology within NASA. .
IT Labs Proof-of-Concept Project: Technical Data Interoperability (TDI) Pathfinder Via Emerging Standards
No known system is in place to allow NASA technical data interoperability throughout the whole life cycle. Life Cycle Cost (LCC) will be higher on many developing programs if action isn't taken soon to join disparate systems efficiently. Disparate technical data also increases safety risks from poorly integrated elements. NASA requires interoperability and industry standards, but breaking legacy ways is a challenge.