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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

Big Data Analytics for Long-Term Meteorological Observations at Hanford Site

A growing number of physical objects with embedded sensors with typically high volume and frequently updated data sets has accentuated the need to develop methodologies to extract useful information from big data for supporting decision making. This study applies a suite of data analytics and core principles of data science to characterize near real-time meteorological data with a focus on extreme weather events. To highlight the applicability of this work and make it more accessible from a risk management perspective, a foundation for a software platform with an intuitive Graphical User Interface (GUI) was developed to access and analyze data from a decommissioned nuclear production complex operated by the U.S. Department of Energy (DOE, Richland, USA). Exploratory data analysis (EDA), involving classical non-parametric statistics, and machine learning (ML) techniques, were used to develop statistical summaries and learn characteristic features of key weather patterns and signatures. The new approach and GUI provide key insights into using big data and ML to assist site operation related to safety management strategies for extreme weather events. Specifically, this work offers a practical guide to analyzing long-term meteorological data and highlights the integration of ML and classical statistics to applied risk and decision science.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Feasibility and benefits of laminar flow control on supersonic cruise airplanes

An evaluation was made of the applicability and benefits of laminar flow control (LFC) technology to supersonic cruise airplanes. Ancillary objectives were to identify the technical issues critical to supersonic LFC application, and to determine how those issues can be addressed through flight and wind-tunnel testing. Vehicle types studied include a Mach 2.2 supersonic transport configuration, a Mach 4.0 transport, and two Mach 2-class fighter concepts. Laminar flow control methodologies developed for subsonic and transonic wing laminarization were extended and applied. No intractible aerodynamic problems were found in applying LFC to airplanes of the Mach 2 class, even ones of large size. Improvements of 12 to 17 percent in lift-drag ratios were found. Several key technical issues, such as contamination avoidance and excresence criteria were identified. Recommendations are made for their resolution. A need for an inverse supersonic wing design methodology is indicated.

Powell, A. G.↗
DOE OSTI2022

Multi-Level Impacts of Extreme Climate-Related Events on Food Supply Chain: Idaho Potato's Case Study

Background: The world is experiencing frequent extreme weather events like droughts, floods, snowstorms, and shifting of seasons due to climate change. Increasing frequencies and severity of these extreme weather events threaten food security because agriculture is extremely vulnerable to climate change. Higher temperature reduces overall yields of the desirable crops but proliferates weeds and harmful pests. Current data shows that every year U.S. farmers spend more than 11 billion USD to fight weeds and this number is expected to rise in the coming years due to climate change. Due to droughts, the water required for irrigation is becoming scarcer. Since many areas are becoming climatically unusable for crop production, the amount of farmland area is shrinking rapidly. In addition, changes in precipitation patterns are causing crop failures and negatively impacting expected yields. In this study, we investigated how different extreme climate events impact different stages of a food supply chain. Approach: As a case study, we chose Idaho’s potato supply chain (SC). Idaho is the top potato producing state in the U.S. and contributes around 30% of the nation’s potato production. Using the agent-based modeling (ABM) approach, we developed a multi-echelon potato supply chain computer simulation model with six types of agents – seed producers, farmers, shippers, processors, retailers, and logistics companies. In addition to the baseline scenario, we developed two additional climate-related disruption events – drought and snowstorm. We investigated how each of these disruption events impacts different stakeholders across the supply chain in terms of revenue and some other key performance metrics such as lead time, food waste, number of delayed orders, and order fulfillment rate. Results: Extreme climate events not only impact the growers but there is also cascading ripple effects downstream of the supply chain. The methodology developed in this study could be applied to other food and agricultural SC to understand the vulnerabilities of the different links. The findings would potentially help to adopt new policies for the well-being of the overall SC.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Lunar calibration and performance assessments of the NOAA-20 VIIRS reflective solar bands

The Moon has played a vital role in the radiometric stability monitoring of NASAs Earth Observing System sensors, such as MODIS on the Terra and Aqua spacecrafts. The lunar calibration methodologies developed for the two MODIS instruments were later extended to apply to the VIIRS instrument on the Suomi-NPP spacecraft. The follow-on VIIRS instrument on the NOAA-20 (N20) spacecraft (previously JPSS-1) has been successfully operating since its launch in November 2017. Fifteen VIIRS spectral bands are in the reflective solar spectral region, covering wavelengths from 0.4 to 2.3 μm. Similar to the previous MODIS and VIIRS instruments, the N20 VIIRS views the Moon via a spacecraft roll maneuver on a near-monthly basis at a confined phase angle range (-51.5° to -50.5°) to facilitate radiometric stability monitoring with reduced uncertainties. In this paper, we briefly present the lunar calibration methodology and also report the derived instrument gain parameters from the regularly scheduled lunar calibrations. The USGS Robotic Lunar Observatory (ROLO) model is used to provide the predicted lunar irradiance for each lunar measurement to account for the variation in the observation geometry. The spatial characterization algorithms using the Moon, previously developed for MODIS and SNPP VIIRS, have also been extended to N20 VIIRS to track its on-orbit band-to-band registration (BBR).

VIIRS↗
NASA NTRS1985

Performance degradation of helicopters due to icing - A review

Methodology developed to predict the performance degradation of rotating systems in natural icing conditions is described and discussed. Theoretical studies of the increments performance degradation due to icing involving the propeller, helicopter in hover and forward flight, and XV-15 propulsion modes are summarized. Related experimental studies on the NACA 0012 airfoil and model helicopter with/without generic ice shapes are reviewed. The results of these experimental and theoretical studies are used to suggest refinements to current methodology.

Korkan, K. D.↗
DOE OSTI2025

Quantifying Climate Change Effects of Bioenergy and BECCS: Critical Considerations and Guidance on Methodology

Bioenergy is a critical element in many national and international climate change mitigation efforts, including as a carbon dioxide removal strategy combined with the capture and durable geological storage of flue gas emissions (BECCS). However, divergent results on the effectiveness of bioenergy as a climate change mitigation measure are reported in the scientific literature. Climate impacts of bioenergy depend on case-specific factors, primarily biophysical features of the biomass production system, and the design and efficiency of conversion and capture processes. Estimates of climate impacts are also strongly affected by methodological choices and assumptions, and much of the divergence between studies derives from differences in the assumed alternate use of the land or feedstock, the alternate energy source and the system boundaries applied. We present a methodology to support robust estimates of the climate change effects of bioenergy systems, updating the standard methodology developed by the International Energy Agency's Technology Collaboration Program on Bioenergy. We provide guidance on the key choices including the reference land use and energy system that bioenergy is assumed to displace, spatial and temporal system boundaries, co-product handling, climate forcers considered, metrics applied and time horizon of impact assessment. Researchers should consider the whole bioenergy system including all life cycle stages, and choose system boundaries, reference systems and treatment of co-products that are consistent with the intended application of the results. The assessment should be normalised to a functional unit that can be compared with other systems delivering an equivalent quantity of the same function. All significant climate forcers should be included, and climate effects should be quantified using appropriate impact assessment methods that distinguish the impact of time. Consistency in methodology and interpretation will facilitate comparison between studies of different bioenergy systems.

09 BIOMASS FUELS↗
NASA NTRS2003

Integrating Oil Debris and Vibration Measurements for Intelligent Machine Health Monitoring

A diagnostic tool for detecting damage to gears was developed. Two different measurement technologies, oil debris analysis and vibration were integrated into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual measurement technologies. This diagnostic tool was developed and evaluated experimentally by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spur Gear Fatigue Rig. An oil debris sensor and the two vibration algorithms were adapted as the diagnostic tools. An inductance type oil debris sensor was selected for the oil analysis measurement technology. Gear damage data for this type of sensor was limited to data collected in the NASA Glenn test rigs. For this reason, this analysis included development of a parameter for detecting gear pitting damage using this type of sensor. The vibration data was used to calculate two previously available gear vibration diagnostic algorithms. The two vibration algorithms were selected based on their maturity and published success in detecting damage to gears. Oil debris and vibration features were then developed using fuzzy logic analysis techniques, then input into a multi sensor data fusion process. Results show combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spur gears. As a result of this research, this new diagnostic tool has significantly improved detection of gear damage in the NASA Glenn Spur Gear Fatigue Rigs. This research also resulted in several other findings that will improve the development of future health monitoring systems. Oil debris analysis was found to be more reliable than vibration analysis for detecting pitting fatigue failure of gears and is capable of indicating damage progression. Also, some vibration algorithms are as sensitive to operational effects as they are to damage. Another finding was that clear threshold limits must be established for diagnostic tools. Based on additional experimental data obtained from the NASA Glenn Spiral Bevel Gear Fatigue Rig, the methodology developed in this study can be successfully implemented on other geared systems.

Dempsey, Paula J.↗
NASA NTRSDate not supplied

Computational Characterization and Model Verification for 3D Microstructure Reconstruction of Additively-Manufactured Materials

The goal of this study is to characterize and validate the texture and grain topology of additively-manufactured anisotropic three-dimensional (3D) polycrystalline microstructures. The special focus is on developing methodologies to compare the grain shapes and orientations of two-dimensional (2D) and 3D microstructure representations using the same metric. To generate statistical data, synthetic microstructures are reconstructed from experimental data using Markov random field (MRF). The statistical similarity between the experimental and synthetic microstructures is verified by comparing their grain topologies. A universal measure to compare 2D and 3D grains is portrayed through the concept of image moments that are invariant to shape transformations. The graphical plots developed based on moment invariants to compare the 2D and 3D grains are used to verify the synthetic model

Materials Characterization↗
DOE OSTI2022

Massively parallel, computationally guided design of a proenzyme

Proteins have shown promise as therapeutics and diagnostics, but their effectiveness is limited by our inability to spatially target their activity. To overcome this limitation, we developed a computationally guided method to design inactive proenzymes or zymogens, which are activated through cleavage by a protease. Since proteases are differentially expressed in various tissues and disease states, including cancer, these proenzymes could be targeted to the desired microenvironment. We tested our method on the therapeutically relevant protein carboxypeptidase G2 (CPG2). We designed Pro-CPG2s that are inhibited by 80 to 98% and are partially to fully reactivatable following protease treatment. The developed methodology, with further refinements, could pave the way for routinely designing protease-activated protein-based therapeutics and diagnostics that act in a spatially controlled manner. Confining the activity of a designed protein to a specific microenvironment would have broad-ranging applications, such as enabling cell type-specific therapeutic action by enzymes while avoiding off-target effects. While many natural enzymes are synthesized as inactive zymogens that can be activated by proteolysis, it has been challenging to redesign any chosen enzyme to be similarly stimulus responsive. Here, we develop a massively parallel computational design, screening, and next-generation sequencing-based approach for proenzyme design. For a model system, we employ carboxypeptidase G2 (CPG2), a clinically approved enzyme that has applications in both the treatment of cancer and controlling drug toxicity. Detailed kinetic characterization of the most effectively designed variants shows that they are inhibited by ∼80% compared to the unmodified protein, and their activity is fully restored following incubation with site-specific proteases. Introducing disulfide bonds between the pro- and catalytic domains based on the design models increases the degree of inhibition to 98% but decreases the degree of restoration of activity by proteolysis. A selected disulfide-containing proenzyme exhibits significantly lower activity relative to the fully activated enzyme when evaluated in cell culture. Structural and thermodynamic characterization provides detailed insights into the prodomain binding and inhibition mechanisms. The described methodology is general and could enable the design of a variety of proproteins with precise spatial regulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Missing data in multi-omics integration: Recent advances through artificial intelligence

Biological systems function through complex interactions between various ‘omics (biomolecules), and a more complete understanding of these systems is only possible through an integrated, multi-omic perspective. This has presented the need for the development of integration approaches that are able to capture the complex, often non-linear, interactions that define these biological systems and are adapted to the challenges of combining the heterogenous data across ‘omic views. A principal challenge to multi-omic integration is missing data because all biomolecules are not measured in all samples. Due to either cost, instrument sensitivity, or other experimental factors, data for a biological sample may be missing for one or more ‘omic techologies. Recent methodological developments in artificial intelligence and statistical learning have greatly facilitated the analyses of multi-omics data, however many of these techniques assume access to completely observed data. A subset of these methods incorporate mechanisms for handling partially observed samples, and these methods are the focus of this review. We describe recently developed approaches, noting their primary use cases and highlighting each method's approach to handling missing data. We additionally provide an overview of the more traditional missing data workflows and their limitations; and we discuss potential avenues for further developments as well as how the missing data issue and its current solutions may generalize beyond the multi-omics context.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1997

Towards a Methodology for Identifying Program Constraints During Requirements Analysis

Requirements analysis is the activity that involves determining the needs of the customer, identifying the services that the software system should provide and understanding the constraints on the solution. The result of this activity is a natural language document, typically referred to as the requirements definition document. Some of the problems that exist in defining requirements in large scale software projects includes synthesizing knowledge from various domain experts and communicating this information across multiple levels of personnel. One approach that addresses part of this problem is called context monitoring and involves identifying the properties of and relationships between objects that the system will manipulate. This paper examines several software development methodologies, discusses the support that each provide for eliciting such information from experts and specifying the information, and suggests refinements to these methodologies.

Romo, Lilly↗
DOE OSTI2023

Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods

The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) is supporting the Geothermal Heating and Cooling Geospatial Datasets and Analysis project conducted by the National Renewable Energy Laboratory (NREL) as part of a broader effort to demonstrate the multi-faceted value of integrating geothermal power and geothermal heating and cooling (GHC) technologies into national decarbonization plans and community energy plans. Currently, there is a need to establish baseline low-temperature geothermal resource datasets and evaluate methods for deploying these technologies to provide the basis for supporting private sector investment. This project is focused on collecting baseline datasets, updating conceptual models, and creating Play Fairway Analysis (PFA) workflows for low-temperature (<150 degrees Celsius) geothermal resources of different geothermal play types (i.e., sedimentary basin, orogenic belts, and radiogenic geothermal play types) that could be used for geothermal heating and cooling (GHC), combined heat and power (CHP), and other geothermal direct uses (GDU) applications. Low-temperature geothermal resources are defined as reservoirs - natural or engineered - with temperatures <150 degrees Celsius. While the focus in the NREL effort is on GHC, resources at the upper end of this temperature range can also be used for small-scale power generation. This project does not include Ground Source Heat Pumps (GSHPs) technologies because they can be effectively developed almost anywhere. Low-temperature geothermal resources have not been studied as extensively as higher- to medium-temperature geothermal resources, but there is recent interest in improving understanding of these types of resources with an uptick of interest in geothermal technologies for decarbonizing heating and cooling systems. In addition, Enhanced Geothermal Systems (EGS) and other emerging technologies for exploiting petrothermal resources have opened the possibility of utilizing deep sedimentary basin systems, where porous media provide permeability and high temperatures can be reached at great depths. This project takes the approach of classifying low- temperature geothermal resources by geothermal play type (GPT). We defined and characterized three major classes of low-temperature GPT: sedimentary basins, orogenic systems, and radiogenic systems. We develop methodologies for evaluating and analyzing the potential for these resources building off the PFA approach to de-risking geothermal exploration and characterization. The proposed PFA approach for low-temperature geothermal resources includes: 1) identifying relevant data (e.g., datasets such bottom-hole temperatures from oil and gas wells, heat flow data, Quaternary faults and stress field data, geophysical data, etc.); 2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, and economic criteria); 3) uncertainty quantification; 4) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and 5) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool (RSAT). This project should facilitate future deployment of GHC, CHP, and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources. Increased deployment of GHC and GDU will help achieve national and local decarbonization goals.

15 GEOTHERMAL ENERGY↗
NASA NTRS1991

Methods development for total organic carbon accountability

This report describes the efforts completed during the contract period beginning November 1, 1990 and ending April 30, 1991. Samples of product hygiene and potable water from WRT 3A were supplied by NASA/MSFC prior to contract award on July 24, 1990. Humidity condensate samples were supplied on August 3, 1990. During the course of this contract chemical analyses were performed on these samples to qualitatively determine specific components comprising, the measured organic carbon concentration. In addition, these samples and known standard solutions were used to identify and develop methodology useful to future comprehensive characterization of similar samples. Standard analyses including pH, conductivity, and total organic carbon (TOC) were conducted. Colorimetric and enzyme linked assays for total protein, bile acid, B-hydroxybutyric acid, methylene blue active substances (MBAS), urea nitrogen, ammonia, and glucose were also performed. Gas chromatographic procedures for non-volatile fatty acids and EPA priority pollutants were also performed. Liquid chromatography was used to screen for non-volatile, water soluble compounds not amenable to GC techniques. Methods development efforts were initiated to separate and quantitate certain chemical classes not classically analyzed in water and wastewater samples. These included carbohydrates, organic acids, and amino acids. Finally, efforts were initiated to identify useful concentration techniques to enhance detection limits and recovery of non-volatile, water soluble compounds.

Benson, Brian L.↗
DOE OSTI2023

Aerodynamic Rotor Design for a 25 MW Offshore Downwind Turbine

Continuously increasing offshore wind turbine scales require rotor designs that maximize power and performance. Downwind rotors offer advantages in lower mass due to reduced potential for tower strike, and is especially true at large scales, e.g., for a 25 MW turbine. In this study, three 25 MW downwind rotors, each with different prescribed lift coefficient distributions were designed (chord, geometry, and twist) and compared to maximize power production at unprecedented scales and Reynolds numbers, including a new approach to optimize rotor tilt and coning based on aeroelastic effects. To achieve this objective the design process was focused on achieving high power coefficients, while maximizing swept area and minimizing blade mass. Maximizing swept area was achieved by prescribing pre-cone and shaft tilt angles to ensure the aeroelastic orientation when the blades point upwards was nearly vertical at nearly rated conditions. Maximizing the power coefficient was achieved by prescribing axial induction factor and lift coefficient distributions which were then used as inputs for an inverse rotor design tool. The resulting rotors were then simulated to compare performance and subsequently optimized for minimum rotor mass. To achieve these goals, a high Reynolds number design space was developed using computational predictions as well as new empirical correlations for flatback airfoil drag and maximum lift. Within this design space, three rotors of small, medium and large chords were considered for clean airfoil conditions (effects of premature transition were also considered but did not significantly modify the design space). The results indicated that the medium chord design provided the best performance, producing the highest power in Region 2 from simulations while resulting in the lowest rotor mass, both of which support minimum LCOE. The methodology developed herein can be used for the design of other extreme-scale (upwind and downwind) turbines.

downwind rotors↗
NASA NTRS2007

SPENVIS Implementation of End-of-Life Solar Cell Calculations Using the Displacement Damage Dose Methodology

This paper presents a method for using the SPENVIS on-line computational suite to implement the displacement damage dose (D(sub d)) methodology for calculating end-of-life (EOL) solar cell performance for a specific space mission. This paper builds on our previous work that has validated the D(sub d) methodology against both measured space data [1,2] and calculations performed using the equivalent fluence methodology developed by NASA JPL [3]. For several years, the space solar community has considered general implementation of the D(sub d) method, but no computer program exists to enable this implementation. In a collaborative effort, NRL, NASA and OAI have produced the Solar Array Verification and Analysis Tool (SAVANT) under NASA funding, but this program has not progressed beyond the beta-stage [4]. The SPENVIS suite with the Multi Layered Shielding Simulation Software (MULASSIS) contains all of the necessary components to implement the Dd methodology in a format complementary to that of SAVANT [5]. NRL is currently working with ESA and BIRA to include the Dd method of solar cell EOL calculations as an integral part of SPENVIS. This paper describes how this can be accomplished.

Walters, Robert↗
NASA NTRS2015

System-Level Experimental Validations for Supersonic Commercial Transport Aircraft Entering Service in the 2018-2020 Time Period

This report describes the work conducted under NASA funding for the Boeing N+2 Supersonic Experimental Validation project to experimentally validate the conceptual design of a supersonic airliner feasible for entry into service in the 2018 -to 2020 timeframe (NASA N+2 generation). The primary goal of the project was to develop a low-boom configuration optimized for minimum sonic boom signature (65 to 70 PLdB). This was a very aggressive goal that could be achieved only through integrated multidisciplinary optimization tools validated in relevant ground and, later, flight environments. The project was split into two phases. Phase I of the project covered the detailed aerodynamic design of a low boom airliner as well as the wind tunnel tests to validate that design (ref. 1). This report covers Phase II of the project, which continued the design methodology development of Phase I with a focus on the propulsion integration aspects as well as the testing involved to validate those designs. One of the major airplane configuration features of the Boeing N+2 low boom design was the overwing nacelle. The location of the nacelle allowed for a minimal effect on the boom signature, however, it added a level of difficulty to designing an inlet with acceptable performance in the overwing flow field. Using the Phase I work as the starting point, the goals of the Phase 2 project were to design and verify inlet performance while maintaining a low-boom signature. The Phase II project was successful in meeting all contract objectives. New modular nacelles were built for the larger Performance Model along with a propulsion rig with an electrically-actuated mass flow plug. Two new mounting struts were built for the smaller Boom Model, along with new nacelles. Propulsion integration testing was performed using an instrumented fan face and a mass flow plug, while boom signatures were measured using a wall-mounted pressure rail. A side study of testing in different wind tunnels was completed as a precursor to the selection of the facilities used for validation testing. As facility schedules allowed, the propulsion testing was done at the NASA Glenn Research Center (GRC) 8 x 6-Foot wind tunnel, while boom and force testing was done at the NASA Ames Research Center (ARC) 9 x 7-Foot wind tunnel. During boom testing, a live balance was used for gathering force data. This report is broken down into nine sections. The first technical section (Section 2) covers the general scope of the Phase II activities, goals, a description of the design and testing efforts, and the project plan and schedule. Section 3 covers the details of the propulsion system concepts and design evolution. A series of short tests to evaluate the suitability of different wind tunnels for boom, propulsion, and force testing was also performed under the Phase 2 effort, with the results covered in Section 4. The propulsion integration testing is covered in Section 5 and the boom and force testing in Section 6. CFD comparisons and analyses are included in Section 7. Section 8 includes the conclusions and lessons learned.

Magee, Todd E.↗
DOE OSTI2023

Assignment of Freight Traffic in a Large-scale Intermodal Network under Uncertainty

This paper presents a methodology for freight traffic assignment in a large-scale road-rail intermodal network under uncertainty. Network uncertainties caused by natural disasters have dramatically increased in recent years. Several of these disasters (e.g., Hurricane Sandy, Mississippi River Flooding, and Hurricane Harvey) severely disrupted the U.S. freight transportation network, and consequently, the supply chain. To account for these network uncertainties, a stochastic freight traffic assignment model is formulated. An algorithmic framework, involving the sample average approximation and gradient projection algorithm, is proposed to solve this challenging problem. The developed methodology is tested on the U.S. intermodal network with freight flow data from the Freight Analysis Framework. The experiments consider three types of natural disasters that have different risks and impacts on transportation networks: earthquakes, hurricanes, and floods. It is found that for all disaster scenarios, freight ton-miles are higher compared to the base case without uncertainty. The increase in freight ton-miles is the highest under the flooding scenario; this is because there are more states in the flood-risk areas, and they are scattered throughout the U.S.

42 ENGINEERING↗
NASA NTRS2012

The Mojave Subsurface Bio-Geochemistry Explorer (MOSBE)

The MOSBE Team has developed a terrestrial field campaign to explore two subsurface biological habitats under the Mojave Desert. This field campaign will not only help us understand terrestrial desert biology, but also will develop methodologies and strategies for potential future Mars missions that would seek to explore the Martian subsurface. We have proposed to the ASTEP program to integrate a suite of field demonstrated instruments with a 20 m subsurface drill as a coherent unit, the Mojave Subsurface Bio-geochemistry Explorer. The ATK Space Modular Planetary Drill System (MPDS) requires no drilling fluid, which allows aseptic sampling, can penetrate lithic ground up to 20 meters of depth, and utilizes less than 100 Watts throughout the entire depth. The drill has been developed and demonstrated in field testing to a depth of 10 meters in Arizona, December 2002. In addition to caching a continuous core throughout the drilling depth, it also generates and caches cuttings and fines that are strata-graphically correlated with the core. As a core segment is brought to the surface, it will be analyzed for texture and structure by a color microscopic imager and for relevant chemistry and mineralogy with a UV fluorescence/Raman spectrometer. Organic and soluble ionic species will be identified through two instruments -- a microcapillary electrophoresis, and an ion trap mass spectrometer that have been developed under PIDDP, ASTID and MIDP funding.

robotic subsurface drilling↗