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At least 397 records · Page 22

Hawai‘i Play Fairway (Final Report)

Most of Hawai'i's geothermal resources are blind—their manifestations, such as hot springs and steam vents, do not appear on the ground surface because the heated water flows far below. With the exception of $K\bar{i}lauea East Rift Zone$, in most areas of Hawai'i, high lateral permeability in the first kilometer below ground surface prevents surface thermal features from developing. As a methodology for discovering these blind resources, Play Fairway Analysis (PFA) involves finding potential locations of blind hydrothermal systems and describing potential geothermal sources in rift-zone settings. Using the PFA to find Hawai'i's geothermal resources, the University of Hawai'i (UH) conducted the Hawai‘i Play Fairway Project, Hawai'i's first statewide geothermal resource assessment since 1985. Sponsored by the U.S. Department of Energy, the Hawai'i Play Fairway Project provided an updated resource assessment, a roadmap for additional exploration activities, and the identification of areas for further exploration. Benefitting from UH's core competency in earth sciences and experienced geothermal researchers, the project comprised three phases. During the first phase, the team identified, compiled, and ranked existing geologic, groundwater, and geophysical datasets relevant to subsurface heat, fluid and permeability. Using a Bayesian statistical approach, the team developed a statistical methodology to integrate these data into a resource probability map. The team evaluated the confidence in the probability value and considered development viability of areas with geothermal resources. With these analyses, the team identified 10 locations in the Hawaiian Islands for exploration activities. For the second phase, the team collected new groundwater data in 10 locations across the state and new geophysical data on $L\bar{a}na‘i, Maui$, and central Hawai'i Island and modeled topographically induced stress to better characterize subsurface permeability. Analyzing the subsurface stresses, the team evaluated the potential for fracture-induced permeability. The team inverted the MT and gravity data to produce 3D models of resistivity and density, respectively, on $L\bar{a}na‘i$, across $Haleakal\bar{a}'s$ SW rift (Maui), and surrounding Mauna Kea (Hawai‘i Island). The team developed and applied a new method for incorporating depth information about resistivity, density, and potential for fracture-induced permeability into the statistical method for computing resource probability in these three focus areas. The team incorporated the new groundwater results with the new geophysical results and the calculations of potential for fracture-induced permeability to produce updated maps of resource probability and confidence. Through combining data from the first and second phases, the team determined locations for further exploration during the third phase. For MT and gravity surveys, the team recommended $Kaua'i's$ $L\bar{i}hu'e$ $Basin$, the east rift of $Maui's$ $Haleakal\bar{a}$ volcano, and the southwest rift of Hawai'i Island's Mauna Loa volcano. The MT and gravity surveys aimed to enable improved confidence in the resource potential in these locations. For drilling deep groundwater well(s), the team recommended Southeast Mauna Kea and $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$. During the third phase, further exploration involved drilling a groundwater well in $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$ and performing more geophysical surveys. We deepened an existing water well proximal to our target area on $L\bar{a}na'i$ due to funding constraints that precluded us from spudding a new well that would exceed 1km depth. Drilling was preceded by a number of substantial elements including: writing an Environmental Assessment and the subsequent legal process, performance of deviation logging, lowering a camera down the well, coordinating site preparation with $P\bar{u}lama$ $L\bar{a}na'i$, shipping the UH-owned rig interisland, procuring supplies, and leading 3 community meetings on $L\bar{a}na'i$. Drilling occurred 24/7 the entire month of June 2019 over which time $L\bar{a}na'i$ $Well$ 10 was deepened from 427 m to 1057 m, with continuous core collected. We measured a roughly linear temperature gradient averaging 42°C/km and a maximum bottom hole temperature of 66°C. This gradient is more than twice the background for Hawai'i and within a range of gradients measured in this depth range for some exploration wells within KERZ. We consider these results encouraging for $L\bar{a}na'i's$ resource potential and recommend following with a slim hole within $L\bar{a}na'i's$ caldera (our target zone) to ~ 2 km. Further, the positive implications such results have for the island of O‘ahu are substantial - the shield stage of O'ahu's volcanoes ended 1-2 My earlier. However, O'ahu uses more electricity than the rest of the islands combined, and the utility recently called for 500-700MW of firm, dispatchable renewable electricity on O'ahu by 2033. In Phase 3, we also collected limited new encouraging groundwater data, and updated our thoughts on the probabilities of fluid and permeability at resource depths (Pr F = 1; Pr P = mostly unconstrained). Ultimately, we advocate for using our final probability of heat, and confidence in this probability, to drive the next phase of exploration. We contend further development of geothermal in Hawai‘i will enable the state to achieve its 100% renewable policy objective and Hawai'i to transition off of fossil fuels through geothermal discovery and development. The project not only produced a large amount of data and expanded the existing knowledge of Hawai'i's geothermal resources, but also produced publications, theses, presentations, core photos, datasets, media reports, television interviews, community events, and a blog. Students and new professionals benefitted from the project's hands-on research experiences and educational opportunities and earned awards and recognition.

15 GEOTHERMAL ENERGY↗

Oxygen, Magnesium, and Aluminum Isotopes in the Ivuna CAI: Re-Examining High-Temperature Fractionations in CI Chondrites

CI chondrites are thought to approximate the bulk solar system composition since they closely match the composition of the solar photosphere. Thus, chemical differences between a planetary object and the CI composition are interpreted to result from fractionations of a CI starting composition. This interpretation is often made despite the secondary mineralogy of CI chondrites, which resulted from low-T aqueous alteration on the parent asteroid(s). Prevalent alteration and the relatively large uncertainties in the photospheric abundances (approx. +/-5-10%) permit chemical fractionation of CI chondrites from the bulk solar system, if primary chondrules and/or CAIs have been altered beyond recognition. Isolated olivine and pyroxene grains that range from approx. 5 microns to several hundred microns have been reported in CI chondrites, and acid residues of Orgueil were found to contain refractory oxides with oxygen isotopic compositions matching CAIs. However, the only CAI found to be unambiguously preserved in a CI chondrite was identified in Ivuna. The Ivuna CAI's primary mineralogy, small size (approx.170 microns), and fine-grained igneous texture classify it as a compact type A. Aqueous alteration infiltrated large portions of the CAI, but other regions remain pristine. The major primary phases are melilite (Ak 14-36 ), grossmanite (up to 20.8 wt.% TiO 2 ), and spinel. Both melilite and grossmanite have igneous textures and zoning patterns. An accretionary rim consists primarily of olivine (Fa 2-17 ) and low-Ca pyroxene (Fs 2-10 ), which could be either surviving CI2 material or a third lithology.

Frank, D. R.↗

Chapter 4: Wind Energy Politics and Economics

A new paradigm for wind energy policy is emerging that is driven by rapidly decreasing costs, increasing market share and the need for more energy system services provided by wind energy. Increased recognition of the diversity of policy needs, tailored to the conditions of each respective jurisdiction, is another significant aspect of this new paradigm. This evolving perspective has come about as onshore wind energy has become the most competitive technology for new energy production in many countries, reducing the need for direct financial support. Accordingly, while the need for wind energy policy support continues, it is becoming increasingly nuanced and focused on serving an array of social objectives associated with the broader evolution of the energy sector. In the future, successful wind energy policies will increasingly be related to creating enabling environments and adapting frameworks, as opposed to focusing on direct investment incentives alone. This reflects a fundamental shift in the perspectives and roles of policy-makers. This is the focus of this chapter, in which we first provide an overview of the state of the art in wind energy policy, followed by upcoming policy challenges and research needs. We conclude with our perspective on the future focus of wind energy policy research.

policy↗

Optical pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

Papers on optical pattern recognition are presented, covering topics such as the estimation of satellite pose and motion parameters using a neural net tracker, associative memory, optical implmentation of programmable neural networks, optoelectronic neural networks, dynamic autoassociative neural memory, heteroassociative memory, bilinear pattern recognition processors, optical processing of optical correlation plane data, and a synthetic discriminant function-based nonlinear optical correlator. Other topics include an interactive optical-digital image processor, geometric transformations for video compression and human teleoperator display, quasiconformal remapping for compensation of human visual field defects, hybrid vision for automated spacecraft landing, advanced symbolic and inference optical correlation filters, and a rotationally invariant holographic tracking system. Additional topics include the detection of rotational and scale-varying objects with a programmable joint transform correlator, a single spatial light modulator binary nonlinear optical correlator, optical joint transform correlation, linear phase coefficient composite filters, and binary phase-only filters.

Liu, Hua-Kuang↗

From following edges to pursuing objects

Primates can generate accurate, smooth eye-movement responses to moving target objects of arbitrary shape and size, even in the presence of complex backgrounds and/or the extraneous motion of non-target objects. Most previous studies of pursuit have simply used a spot moving over a featureless background as the target and have thus neglected critical issues associated with the general problem of recovering object motion. Visual psychophysicists and theoreticians have shown that, for arbitrary objects with multiple features at multiple orientations, object-motion estimation for perception is a complex, multi-staged, time-consuming process. To examine the temporal evolution of the motion signal driving pursuit, we recorded the tracking eye movements of human observers to moving line-figure diamonds. We found that pursuit is initially biased in the direction of the vector average of the motions of the diamond's line segments and gradually converges to the true object-motion direction with a time constant of approximately 90 ms. Furthermore, transient blanking of the target during steady-state pursuit induces a decrease in tracking speed, which, unlike pursuit initiation, is subsequently corrected without an initial direction bias. These results are inconsistent with current models in which pursuit is driven by retinal-slip error correction. They demonstrate that pursuit models must be revised to include a more complete visual afferent pathway, which computes, and to some extent latches on to, an accurate estimate of object direction over the first hundred milliseconds or so of motion.

NASA Discipline Neuroscience↗

Neural networks application to divergence-based passive ranging

The purpose of this report is to summarize the state of knowledge and outline the planned work in divergence-based/neural networks approach to the problem of passive ranging derived from optical flow. Work in this and closely related areas is reviewed in order to provide the necessary background for further developments. New ideas about devising a monocular passive-ranging system are then introduced. It is shown that image-plan divergence is independent of image-plan location with respect to the focus of expansion and of camera maneuvers because it directly measures the object's expansion which, in turn, is related to the time-to-collision. Thus, a divergence-based method has the potential of providing a reliable range complementing other monocular passive-ranging methods which encounter difficulties in image areas close to the focus of expansion. Image-plan divergence can be thought of as some spatial/temporal pattern. A neural network realization was chosen for this task because neural networks have generally performed well in various other pattern recognition applications. The main goal of this work is to teach a neural network to derive the divergence from the imagery.

Barniv, Yair↗

The United States digital recording industry

The recording industry resembles the semiconductor industry in several aspects. Both are large (greater than $60 Billion/year revenues); both are considered critical technologies supporting national objectives; both are experiencing increased competition from foreign suppliers; they recognize significant opportunities for both technological and market growth in the decade to come; and both realize that a key to this future growth lies in alliances among industry, academia, and government. The semiconductor industry has made significant investments in alliances relating to manufacturing technologies (SEMATECH) and to joint long-term technology research centered in universities (SRC). The federal government has provided funding support of these efforts in recognition of the critical roles semiconductor technologies play in national interests. The recording industry is now also forming critical alliances, but has been slower in starting and in gaining broad recognition by government agencies and legislators that the industry needs federal support. Traditionally, the recording industry has been viewed as mature, stable, and, while critical to national interests, able to chart and fund its own course toward future national needs. That perception is fortunately changing.

Simonds, John L.↗

Structured information extraction from scientific text with large language models

Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned to extract useful records of complex scientific knowledge. We test three representative tasks in materials chemistry: linking dopants and host materials, cataloging metal-organic frameworks, and general composition/phase/morphology/application information extraction. Records are extracted from single sentences or entire paragraphs, and the output can be returned as simple English sentences or a more structured format such as a list of JSON objects. This approach represents a simple, accessible, and highly flexible route to obtaining large databases of structured specialized scientific knowledge extracted from research papers.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Bioprocessing development: Immune/cellular applications: Anti-Ig autoantibody and complement-mediated destruction of neoplastic cells

This space bioprocessing contract effort was comprised of four general objectives. These were: (1) the evaluation of current separation processes, (2) the identification of problems relevant to the separation of important biologicals, (3) the identification of ground-based assay methods needed for pre- and postflight analysis of space bioprocessing separation technology; and (4) the establishment of methods to determine the efficiency of space bioprocessing separation procedures. Immunology was deemed advantageous to study the diversity of cells and cell products involved and the extensive interest being given to their separation. Upon recognition of a cellular or molecular agent as foreign to the body, the immune system becomes activated to produce cells whose function is to destroy that agent and cell products whose function is to inactivate the agent and assist in its destruction. Long after the agent is removed from the body, some cells remain in a state of readiness to continue these destructive actions specifically against that agent should further exposure to it occur. This is the basis of acquired immunity to disease.

Twomey, J. J.↗

Acoustical and Intelligibility Test of the Vocera(Copyright) B3000 Communication Badge

To communicate with each other or ground support, crew members on board the International Space Station (ISS) currently use the Audio Terminal Units (ATU), which are located in each ISS module. However, to use the ATU, crew members must stop their current activity, travel to a panel, and speak into a wall-mounted microphone, or use either a handheld microphone or a Crew Communication Headset that is connected to a panel. These actions unnecessarily may increase task times, lower productivity, create cable management issues, and thus increase crew frustration. Therefore, the Habitability and Human Factors and Human Interface Branches at the NASA Johnson Space Center (JSC) are currently investigating a commercial-off-the-shelf (COTS) wireless communication system, Vocera(C), as a near-term solution for ISS communication. The objectives of the acoustics and intelligibility testing of this system were to answer the following questions: 1. How intelligibly can a human hear the transmitted message from a Vocera(c) badge in three different noise environments (Baseline = 20 dB, US Lab Module = 58 dB, Russian Module = 70.6 dB)? 2. How accurate is the Vocera(C) badge at recognizing voice commands in three different noise environments? 3. What body location (chest, upper arm, or shoulder) is optimal for speech intelligibility and voice recognition accuracy of the Vocera(C) badge on a human in three different noise environments?

Archer, Ronald↗

Transcribing Air Traffic Control System Command Center Planning Telecons Using Cloud-Based Automatic Speech Recognition

This paper addresses the challenge of using Automatic Speech Recognition (ASR) technology to transcribe regular teleconferences that happen between FAA Air Traffic Control System Command Center (ATCSCC) planners, stakeholders and air users. These planning teleconferences (aka telecons or planning webinars) are an integral part of managing air traffic in the U.S. National Airspace System (NAS). In particular, the meetings facilitate the creation and modification of various traffic management initiatives (TMIs), that are used to regulate the flow of air traffic. This is typically a human intensive process, requiring specialists to listen to the entire meeting audio (10-20 minutes duration) and inferring the state of the NAS (e.g., weather phenomenon) that was discussed. It would be advantageous to have digital transcripts of the audio and have useful information (e.g., related to TMIs) automatically extracted from the transcripts. In this regard, we are exploring the adoption of state-of-the-art speech to text and Natural Language Processing (NLP) tools that will achieve our objective of digitizing the webinar audio. Unfortunately, the highly technical phraseology present in the audio and limited data availability for model building make ASR difficult. To overcome this challenge, we have taken the critical first step in creating a human transcription dataset from ~20 hours of speech in the ATCSCC audio with the help of subject matter experts. A novelty of our work is the creation of a ground truth transcription dataset for ATCSCC teleconference webinars, which is particularly important for Aviation domain-specific NLP tasks. Using Microsoft Speech Studio, a cloud-based ASR platform, we have fine-tuned the English pre-trained ASR models (available in speech studio) and achieved an average word error rate (WER) of 6.81%. The baseline ASR also provides a digital version of each planning webinar, making it accessible and text-searchable for future references. Additionally, the transcriptions can serve as a bridge between raw audio data and a range of text-based NLP tasks, such as named entity recognition (NER) and intent classification, potentially enhancing the digital footprint of the webinars and other connected data sources. Our work has several potential applications. Firstly, the transcriptions can be analyzed to understand the complex decision process of creating, implementing and modifying TMIs and may also contribute to TMI prediction services. Secondly, our dataset and model can be used to develop more accurate ASR systems for aviation-specific language, which can bring about digital communication in the aviation industry (and aid current “voice only” communications, which are inherently error-prone). Lastly, the transcriptions themselves can be used as a valuable resource for training other NLP models.

Stephen S. B. Clarke↗

Pulsations, Shocks, and Mass Loss

This grant provided long-term support for my investigation of the outflows powered by young stars. Several major research results emerged during the course of this research, including: (1) The discovery of giant Herbig-Haro outflows from young stars that can extend for many parsecs from their sources. The first parsec-scale outflow to be recognized led to the realization that Herbig-Haro outflows, even those produced by low mass young stellar objects, can extend orders of magnitude farther from their sources than previously thought. Our preconceptions were to a large extent driven by the narrow fields-of-view then provided by CCD detectors. With the recent advent of large format CCDs and CCD mosaics, we have come to realize that most outflows attain parsec-scale dimensions. Even at the distance of the Orion star forming clouds, such flows can subtend a degree on the sky. Our work has led to the recognition of over two dozen giant. (2) The discovery that outflows are highly clustered. Even regions of relatively isolated star formation such as those in Taurus frequently produce multiple outflows. (3) The discovery of a new family of externally irradiated jets. During the last year of support from this grant, we made the startling discovery that there is a class of jets from young stars that are illuminated by the ionizing radiation field of nearby massive stars. The first four examples were discovered in the vicinity of the a Orionis sub-group of the Orion OB Association which is believed to be at least 2 million years old. Since the jets are photo-ionized, their densities can be reliably estimated. Most HH jets are shock excited, and are therefore notoriously difficult to characterize since their visibility and observed properties depend on the complex and highly non-linear processes associated with shocks. Furthermore, many irradiated jets are one sided rather than bipolar. Thus, irradiated jets may for the first time be used to accurately diagnose jet densities and mass loss rates, and to probe the physics of jet collimation, and may indicate that the jet production phase of certain young stars may last more than a million years. These three discoveries provide us with fundamental new insights into the star formation process, into the physical conditions inside and near star forming clouds, and into new ways to probe the physics and chemistry of such clouds.

Bally, John↗

Results from the crop identification technology assessment for remote sensing /CITARS/ project

The CITARS (Crop Identification Technology Assessment for Remote Sensing) task design, objectives, and results are reviewed along with relevant conclusions and recommendations. The principal assessment concern crop identification performance for corn and soybeans in six sites in Illinois and Indiana. Use of quantitative measures of classification performance and statistical evaluations of the results have been important parts of the technology assessment. Relation of crop and sensor characteristics is discussed. Factors affecting crop identification performance are identified as crop maturity and site characteristics, type of single-date automatic data processing procedure used for local recognition, nonlocal recognition with and without processing for extension of recognition signatures, and use of multidate or multitemporal data. In particular, the probability of correct classification of field center pixels is not well correlated and thus is not a reliable indicator of proportion estimation performance.

Bizzell, R. M.↗

SolSmart Technical Assistance Provider (Final Technical Report)

The SolSmart program was established in late 2015 to “establish a prominent national recognition and technical assistance program for local governments that will signal to installers and the public that a community is receptive to solar businesses and has established a supportive solar market environment. This, in turn, will reduce market barriers and lower soft costs, thus contributing to SunShot goals. The program will also assist communities who are just beginning to improve their solar markets.” By March 31, 2022 (the grant end date), the SolSmart Team designated 460 communities, more than 50% more than the initial program objective of 300 communities. The designated communities represent 42 states, the District of Columbia, the U.S. Virgin Islands, and Puerto Rico. The SolSmart team developed and revised criteria representing best practices for local governments; recruited, trained, evaluated, and mentored communities to incorporate these best practices; and disseminated resources about solar and solar-related technologies as well as the newest best practices on a regular basis. 98% of local government officials who participated in the program said that SolSmart increased their knowledge of solar energy. The SolSmart program had both real and perceived tangible impacts on barriers to solar adoption in designated communities. Significantly, the time to permit a solar installation decreased by 7.5 days on average. This reduced the soft costs for both the solar installer (and therefore the customer) and the local government. The result is that solar installations in SolSmart communities increased by 17% per month compared with similar non-SolSmart communities. Larger and wealthier communities were more likely to pursue SolSmart designation and earn more points within SolSmart. As a result, IREC/TSF developed strategies to reach underserved communities and created new resources to help them more easily achieve designation, as described below. In the last year of the Award, 44% of designated communities were underserved, compared with 31% in the earlier years of the program. DOE issued two awards for SolSmart: the SolSmart Technical Assistance Provider (TAP), led by The Solar Foundation (TSF) which has since merged with the Interstate Renewable Energy Council (IREC), and the Designation Program Administrator (DPA), led by the International City/County Management Association (ICMA). IREC was lead for the TAP project and, until the time of TSF/IREC merger, was a subrecipient on the DPA project. These two projects were interdependent; one could not exist without the other. While this report will focus on the work performed by the TAP, it will be impossible to speak of this without talking about the successes, impacts, and benefits of the overall SolSmart program.

14 SOLAR ENERGY↗

Stanford/NASA-Ames Center of Excellence in model-based human performance

The human operator plays a critical role in many aeronautic and astronautic missions. The Stanford/NASA-Ames Center of Excellence in Model-Based Human Performance (COE) was initiated in 1985 to further our understanding of the performance capabilities and performance limits of the human component of aeronautic and astronautic projects. Support from the COE is devoted to those areas of experimental and theoretical work designed to summarize and explain human performance by developing computable performance models. The ultimate goal is to make these computable models available to other scientists for use in design and evaluation of aeronautic and astronautic instrumentation. Within vision science, two topics have received particular attention. First, researchers did extensive work analyzing the human ability to recognize object color relatively independent of the spectral power distribution of the ambient lighting (color constancy). The COE has supported a number of research papers in this area, as well as the development of a substantial data base of surface reflectance functions, ambient illumination functions, and an associated software package for rendering and analyzing image data with respect to these spectral functions. Second, the COE supported new empirical studies on the problem of selecting colors for visual display equipment to enhance human performance in discrimination and recognition tasks.

Wandell, Brian A.↗

[NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 7:] The NASA/DOD Aerospace Knowledge Diffusion Research Project: The DOD perspective

This project will provide descriptive and analytical data regarding the flow of STI at the individual, organizational, national, and international levels. It will examine both the channels used to communicate information and the social system of the aerospace knowledge diffusion process. Results of the project should provide useful information to R and D managers, information managers, and others concerned with improving access to and use of STI. Objectives include: (1) understanding the aerospace knowledge diffusion process at the individual, organizational, and national levels, placing particular emphasis on the diffusion of Federally funded aerospace STI; (2) understanding the international aerospace knowledge diffusion process at the individual and organizational levels, placing particular emphasis on the systems used to diffuse the results of Federally funded aerospace STI; (3) understanding the roles NASA/DoD technical report and aerospace librarians play in the transfer and use of knowledge derived from Federally funded aerospace R and D; (4) achieving recognition and acceptance within NASA, DoD and throughout the aerospace community that STI is a valuable strategic resource for innovation, problem solving, and productivity; and (5) providing results that can be used to optimize the effectiveness and efficiency of the Federal STI aerospace transfer system and exchange mechanism.

Pinelli, Thomas E.↗

Investigation of Error Patterns in Geographical Databases

The objective of the research conducted in this project is to develop a methodology to investigate the accuracy of Airport Safety Modeling Data (ASMD) using statistical, visualization, and Artificial Neural Network (ANN) techniques. Such a methodology can contribute to answering the following research questions: Over a representative sampling of ASMD databases, can statistical error analysis techniques be accurately learned and replicated by ANN modeling techniques? This representative ASMD sample should include numerous airports and a variety of terrain characterizations. Is it possible to identify and automate the recognition of patterns of error related to geographical features? Do such patterns of error relate to specific geographical features, such as elevation or terrain slope? Is it possible to combine the errors in small regions into an error prediction for a larger region? What are the data density reduction implications of this work? ASMD may be used as the source of terrain data for a synthetic visual system to be used in the cockpit of aircraft when visual reference to ground features is not possible during conditions of marginal weather or reduced visibility. In this research, United States Geologic Survey (USGS) digital elevation model (DEM) data has been selected as the benchmark. Artificial Neural Networks (ANNS) have been used and tested as alternate methods in place of the statistical methods in similar problems. They often perform better in pattern recognition, prediction and classification and categorization problems. Many studies show that when the data is complex and noisy, the accuracy of ANN models is generally higher than those of comparable traditional methods.

Dryer, David↗

Free-Flight Terrestrial Rocket Lander Demonstration for NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) System

The Autonomous Landing Hazard Avoidance Technology (ALHAT) Project is chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. The ALHAT System must be capable of identifying and avoiding surface hazards to enable a safe and accurate landing to within tens of meters of designated and certified landing sites anywhere on a planetary surface under any lighting conditions. Since its inception in 2006, the ALHAT Project has executed four field test campaigns to characterize and mature sensors and algorithms that support real-time hazard detection and global/local precision navigation for planetary landings. The driving objective for Government Fiscal Year 2012 (GFY2012) is to successfully demonstrate autonomous, real-time, closed loop operation of the ALHAT system in a realistic free flight scenario on Earth using the Morpheus lander developed at the Johnson Space Center (JSC). This goal represents an aggressive target consistent with a lean engineering culture of rapid prototyping and development. This culture is characterized by prioritizing early implementation to gain practical lessons learned and then building on this knowledge with subsequent prototyping design cycles of increasing complexity culminating in the implementation of the baseline design. This paper provides an overview of the ALHAT/Morpheus flight demonstration activities in GFY2012, including accomplishments, current status, results, and lessons learned. The ALHAT/Morpheus effort is also described in the context of a technology path in support of future crewed and robotic planetary exploration missions based upon the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN).

Rutishauser, David K.↗