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A method for displaying large amounts of information. The method includes the steps of forming a spatial layout of tiles each corresponding to a representative reference element; mapping observed elements onto the spatial layout of tiles of representative reference elements; assigning a respective value to each respective tile of the spatial layout of the representative elements; and displaying an image of the spatial layout of tiles of representative elements. Each tile includes atomic attributes of representative elements. The invention also relates to an apparatus for displaying large amounts of information. The apparatus includes a tiler forming a spatial layout of tiles, each corresponding to a representative reference element; a comparator mapping observed elements onto said spatial layout of tiles of representative reference elements; an assigner assigning a respective value to each respective tile of said spatial layout of representative reference elements; and a display displaying an image of the spatial layout of tiles of representative reference elements.
Here, this study develops the sparse chronology method to enhance the representative period framework in capacity expansion models, enabling the effective integration of long-duration energy storage modeling. Traditional representative period methods cannot capture the state of charge of seasonal energy storage systems because they do not establish effective inter-day linkages to connect the state of charge between periods. The sparse chronology approach addresses this limitation by establishing inter-day linkages that allow state of charge to shift inter-seasonally. At the same time, it groups identical representative days into partitions, applying constraints sparsely and implicitly to reduce computational load further. Validation results demonstrate that this method successfully simulates long-duration energy storage patterns, achieving close alignment with a continuous yearly benchmark model, with seasonal trends and state of charge cycles clearly represented. The computational load analysis reveals that the sparse chronology method efficiently applies constraints on maximum and minimum state of charge limits within the representative day framework, eliminating the need for detailed constraints on each individual day. By partitioning representative days and constraining only the start and end of each partition, the method significantly decreases computational requirements. Simulation results show that sparse chronology closely approximates the continuous yearly method's accuracy, even with as few as 20 representative days, achieving correlation values with the benchmark of nearly 0.9 in state of charge plots. Furthermore, it maintains computational efficiency, requiring only 4 % of the solver time compared to the continuous yearly method with 20 representative days. This approach allows capacity expansion models to incorporate long-duration energy storage with high temporal, spatial, and technological resolution, enabling more detailed modeling for large-scale power systems.
This data product represents the integration of new code capability for arctic tundra hillslope hydrologic processes into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The current ELM represents water movement primarily through vertical processes, such as precipitation, canopy interception, evaporation, infiltration, and soil water movement. Lateral water movement—such as surface runoff, subsurface flow, and river transport—plays a significant role in the hydrological cycle, especially in regions with varied topography. While E3SM includes a runoff routing component representing water transport in the river network, the lateral transport of water at the subgrid scale within the land model has previously not been taken into account. With the recent development of topographic units within the ELM subgrid data structure, there is an opportunity to simulate hillslope hydrologic connectivity by introducing water transport along topographic gradients. We expect that more realistic representation of hillslope hydrologic processes will lead to improved predictions of both soil water content and river network flows. Lateral transport of water at and near the surface is represented as a sub-grid process in this new code development. Water is tracked as it moves from higher to lower elevations within a gridcell. This capability uses the nested hierarchical sub-grid scheme within ELM to connect water fluxes from sub-grid elements with higher elevation to those with lower elevation. This data record consists of a single document (pdf format) that describes the theoretical basis for the hillslope hydrology processes added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required to represent the ejected foam. The exponents were evaluated by least squares method from experimental data. The equation is used and it can represent multiple factors in other problems as well; for example, evaluation of fatigue life, creep life, fracture toughness, and structural fracture, as well as optimization functions. The software is rather simplistic. Required inputs are initial value, final value, and an exponent for each factor. The number of factors is open-ended. The value is updated as each factor is evaluated. If a factor goes to zero, the previous value is used in the evaluation.
The ability to match two scenes is a fundamental requirement in a variety of computer vision tasks. A graph theoretic approach to inexact scene matching is presented which is useful in dealing with problems due to imperfect image segmentation. A scene is described by a set of graphs, with nodes representing objects and arcs representing relationships between objects. Each node has a set of values representing the relations between pairs of objects, such as angle, adjacency, or distance. With this method of scene representation, the task in scene matching is to match two sets of graphs. Because of segmentation errors, variations in camera angle, illumination, and other conditions, an exact match between the sets of observed and stored graphs is usually not possible. In the developed approach, the problem is represented as an association graph, in which each node represents a possible mapping of an observed region to a stored object, and each arc represents the compatibility of two mappings. Nodes and arcs have weights indicating the merit or a region-object mapping and the degree of compatibility between two mappings. A match between the two graphs corresponds to a clique, or fully connected subgraph, in the association graph. The task is to find the clique that represents the best match. Fuzzy relaxation is used to update the node weights using the contextual information contained in the arcs and neighboring nodes. This simplifies the evaluation of cliques. A method of handling oversegmentation and undersegmentation problems is also presented. The approach is tested with a set of realistic images which exhibit many types of sementation errors.
Martian basalts represented by the shergottite meteorites reflect derivation from highly depleted mantle sources (high Nd, strong LREE depletions, low fO2)[1-3], with evidence of mixing with a much more enriched and oxidized reservoir, most likely a late-stage product of crystallization of an initial martian magma ocean [3-6]. The martian basaltic meteorites Yamato 980459 (Y98) and QUE 94201 (QUE) have bulk compositions that appear to represent bonafide liquids, rather than products of protracted crystallization. These two meteorites also represent the most primitive and evolved examples of the depleted basaltic shergottite suite. Magmatic liquids serve as effective probes of their source regions, and thus studying the potential relationship between magmas represented by Y98 and QUE can yield important information on the formation and evolution of martian basalts. Although the ages of these meteorites preclude that they are petrogenetically related to each other, they represent the best existing candidates for genuine liquids (other meteorites are suggested to represent liquid compositions, including LAR 06319 [7] and NWA 5789 [8], but only Y98 and QUE have been verified experimentally). They span much of the bulk-compositional range of martian basaltic meteorites, and represent end-member liquid compositions likely to arise from partial melting of the martian mantle. Recent efforts to model Y98-like parent liquid evolution by fractional crystallization using MELTS [6] produced a derivative liquid composition that closely matches QUE bulk composition, although it required a some-what unusual crystallization sequence. Experimental endeavours to verify this result at 1 bar have, however, been inconclusive [9].
The first year’s effort identified sampling and interviewing as the principal risks to assessment of prompt reactions to overflights producing low-amplitude sonic booms. It also 1) established the utility of geo-information system-based route planning for LBFD flight missions, 2) developed and demonstrated a prototype of a geographically-distributed, Internet-enabled instrumentation system capable of wide-area tracking of LBFD aircraft in near-real time. The latter system permits synchronizing the conduct of interviews in multiple overflown communities with arrival times of shock waves at interviewing sites; and of measuring, archiving, and processing their acoustic signatures. Means were also recommended for constructing representative, telephone-based samples of eligible respondents living in households within carpet boom corridors adjacent to LBFD flight tracks, and for conducting interviews with cross-sectional (independent) samples of such respondents about their prompt reactions to exposure to low-amplitude sonic booms. A detailed study design was prepared and accepted by NASA for a set of single-contact attempt telephone interviews with a nationally representative sample of households. The study design focused on testing automated and live agent interview completion rates obtainable without callbacks. A minimal (two monitoring station) version of the aircraft tracking system was built and installed near a civil airport in a successful demonstration of the system’s ability to detect and track aircraft movements. The field exercise also demonstrated the ability of the system to capture the acoustic emissions of departing aircraft, and to serve aircraft position and sound level information to remote, geographically-distributed analysts in near-real time. Upon approval of OMB and IRB of the detailed study plan, a stratified, nationally representative sample of landline and wireless telephone-subscribing households was constructed. A total of 12,734 telephone interview contact attempts of the sort required by a straightforward cross-sectional study design were then made. These contact attempts demonstrated the impracticality of conducting a time-critical, cross-sectional study of prompt community response to low-amplitude sonic booms by means of “independent” (single contact attempt per respondent for each LBFD flight mission) telephone samples of respondents. The observed interview completion rates for these single telephone contact attempts were so low (~ 1% to 3% for automated and live agent interviews, respectively) that: 1) the representativeness of collected opinions would be susceptible to intuitive challenge as inadequate, even absent conclusive evidence of non-representativeness. Refuting challenges to representativeness would have to demonstrate that the composition of the actual sample did not differ from that of the target population, a task that is tantamount to proving a negative; 2) the information required to refute allegations of non-representativeness would require a questionnaire considerably lengthier than that required simply to determine the prevalence of boom-induced startle and annoyance. Such a questionnaire would have to inquire about potentially sensitive and intrusive matters, including respondents’ age, gender, education, employment, home ownership, income, ethnicity, family size, and other demographic factors; and 3) unreasonable numbers of attempts would be required to re-contact households with unsuccessful initial contact attempts, given the limited time available for doing so. For example, if about 500 completed interviews were desired in a supersonically overflown community, approximately 50,000 automated interview attempts would have to be made within ten to fifteen minutes of each LBFD overflight. Such large numbers of contact attempts could well exceed the numbers of households available for interview in areas of similar boom exposure levels in some communities near LBFD flight tracks. Such large numbers of interviews could be cost-effectively undertaken only by means of automated (i.e., outgoing interactive voice response) interviewing, a data collection method ill-suited for complex and sensitive questionnaire items. The infeasibility of independent sampling for evaluating prompt responses to LBFD overflights in a cross-sectional study is due in large part to simple non-response: that is, potential respondents – particularly those contacted on wireless telephones – refusing to answer calls with unfamiliar caller IDs. It is also due in part, however, to 1) the lack of time to attempt to contact the same respondent more than once within a few minutes after the arrival of a shock wave at the respondent’s location; and 2) the need to place calls during weekday/daytime hours, when response rates are notably lower than during evenings and weekends. Despite the poor interview completion rates achieved under the above constraints, cross sectional assessments of delayed reactions to LBFD overflights could still be feasible, if multiple attempts could be made to contact respondents during evening and weekend time periods, over extended time periods. Detailed plans for a longitudinal (panel) sample were developed as an alternative to a cross sectional sample design.
In an effort to create a base and foundation for ASSEMBLERS with an informed layout, data representing the range of motion of varying heights of Stewart platforms were analyzed. 3D shapes were generated first to be approximately representative of these data in the form of rotationally symmetric shells, making use of 2D alpha shapes to create a border that did not account for asymmetry inherent in the true range of motion. Further work was performed to generate mesh files more fully representative of reach, creating 3D alpha shapes based directly on point clouds generated from uniformly random platform positions. These shapes were initially not representative of the entire range of motion of a platform stack due to the low likelihood of the most extreme positions being added to a given point cloud but were more representative of the asymmetry inherent in the possible positions of a Stewart platform as they no longer relied on a single 2D contour. The same algorithm for generating 3D alpha shapes was then applied to point clouds designed to represent extreme positions, generating larger smooth shells with six clear planes of symmetry. All shells were converted to STLs to aid in further modeling of range of motion for base layouts and in visualizing reachable area for varying stack heights, successfully creating closed shells representative of typical and extreme positions for platform stacks of varying heights.
The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25-100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.
This dataset was generated using an iterative active-learning strategy implemented in the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials for aqueous ZnCl2 solutions. Each active-learning cycle consisted of three stages: training, exploration, and labeling. The initial training set combined configurations generated in this work from enhanced-sampling ab initio molecular dynamics simulations with configurations from a previously reported neural-network-potential study of aqueous ZnCl2. The enhanced-sampling ab initio molecular dynamics simulations involved Zn–Cl separation and the chloride coordination number around Zn²? as collective variables. These configurations served as the seed dataset. Subsequent active-learning cycles expanded the training set by identifying and labeling configurations that were poorly represented by the current models, thereby improving coverage of ion-association states and changes in local coordination and charge-state environments relevant to the solution free-energy landscape. For all selected configurations, single-point calculations of the total energies and atomic forces were performed within density functional theory using the CP2K Quickstep module. Reference calculations employed the revPBE-D3 and r2SCAN exchange-correlation functionals. Motivated by recent work on aqueous Zn²?, the main revPBE calculations omitted D3 dispersion contributions involving Zn²?, while retaining the D3 correction for water and chloride. For comparison, fully dispersion-corrected revPBE-D3 reference calculations were also performed, with D3 applied to all species, including Zn²?. Valence electrons were treated explicitly, while core electrons were represented using norm-conserving Goedecker–Teter–Hutter pseudopotentials. The wave functions were expanded using the mixed Gaussian-and-plane-wave scheme with TZV2P-MOLOPT basis sets for all elements and a 600 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent-field convergence was accelerated using the orbital-transformation and Direct Inversion in the Iterative Subspace algorithms, with a convergence threshold of 10?6. All single-point calculations were performed in periodic orthorhombic cells. The CELL_REF keyword in CP2K was used to define a fixed reference cell with a box length of 25 Å. This treatment ensured a consistent reference for configurations extracted from NpT trajectories with fluctuating cell dimensions. The resulting DFT energies and atomic forces constitute the ground-truth labels used to train the MLIPs. The resulting MLIP was trained for aqueous ZnCl2 solutions spanning concentrations from 0 to 30 molal and a broad pH range, from strongly acidic to strongly basic conditions. Representative examples of configurations included in the MLIP training dataset are provided below. These include 1) Representative configurations from the dataset labeled at the revPBE-D3 level, with D3 dispersion interactions involving Zn2+ excluded (revPBE-wo-D3). 2) Representative configurations from the dataset labeled at the fully dispersion-corrected revPBE-D3 level, with D3 interactions applied to all species, including Zn2+ (revPBE-D3). 3) Representative configurations from the dataset labeled at the r2SCAN level of theory (r2SCAN).
The presence of warm boundary layer stratiform clouds over the eastern North Atlantic (ENA) region is commonly influenced by the Azores High, especially during the summer season. To investigate comprehensive aerosol–cloud interactions, this study employs the Weather Research and Forecasting model coupled with a chemistry component (WRF-Chem), incorporating aerosol chemical components that are relevant to the formation of cloud condensation nuclei (CCN) and accounting for aerosol spatiotemporal variation. This study focuses on aerosol indirect effects, particularly the long-range transport of aerosols, in the ENA region under three different weather regimes: a ridge with a surface high-pressure system, a post-trough with a surface high-pressure system, and a weak trough. The WRF-Chem simulations conducted at a near-large-eddy scale offer valuable insights into the model's performance, especially in terms of its ability to use high spatial resolution to capture mesoscale cloud features across various weather regimes. Our result shows that introducing 5 times more aerosols to either non-precipitating or precipitating clouds significantly increases ambient CCN numbers, resulting in, to varying degrees, higher liquid water path (LWP) values. The substantial aerosol–cloud interaction especially occurs in the precipitating clouds and demonstrates the susceptibility of the LWP to changes in CCN under different regimes. Conversely, thin, non-rain clouds at the edges of a cloud system are prone to evaporation, exhibiting an aerosol drying effect. The aerosols released during this process transition back to the accumulation mode, facilitating future activation. This dynamic behavior is not adequately represented in prescribed-aerosol simulations.
Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection Description This dataset contains input and output data for the manuscript Mongird, K. et al. (under review) titled "Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection". Input data corresponds to gridded spatial siting attributes that are necessary to conduct a random forest machine learning analysis of siting feature importance. Output data includes SHAP feature analysis outputs, and classification report values. For data on power plant siting results referred to in the manuscript, please refer to the CERF: IM3 Projected Western US Power Plant Locations data download page. The downloadable data includes values for eight different future scenarios for the Western US. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 Technical Information The dataset includes two sets of data files: (1) CERF gridded siting parameters and (2) Feature analysis outputs and classification reports. All downloadable data is in csv file format. Files with x/y coordinate information use the Albers Equal Area Conic projection (ESRI:102003). 1. CERF Gridded Siting Parameters This directory provides a balanced sample of gridded CERF siting parameters data for eight different scenarios for the Western US through 2055, seven different technologies, and eight timesteps. This data serves as input to the feature analysis. It contains the following parameters. region_name - name of region (i.e., state) sited - binary value representing whether the grid cell received a siting of that technology type (1=True) rcp - binary value representing scenario resource concentration pathway (0 = RCP4.5, 1 = RCP8.5) ssp - binary value representing scenario shared socioeconomic pathway (0 = SSP3, 1 = SSP5) climate - binary value representing cooler (0) or hotter (1) GCM forcing tech_name - generation technology name sited_year - year that values correspond to transmission_cost - cost of transmission interconnection pipeline_cost - cost of natural gas pipeline interconnection interconnection_cost - total interconnection cost (sum of transmission cost and gas pipeline cost) lmp - associated locational marginal value ($/MWh) associated with the grid cell, timestep, scenario, and technology xcoord - x-coordinate of location ycoord - y-coordinate of location 2a. Feature Analysis Output The dataset includes the feature analysis shap output for locational marginal price and interconnection cost. It contains the following parameters. technology - generator technology name scenario - name of scenario feature - name of feature, either locational_marginal_price or interconnection_cost value - the mean of absolute value of SHAP values for given feature 2b. Feature Analysis Classification Report This download includes the classification report associated with each random forest model. The dataset contains the following parameters. technology - generation technology name scenario - name of scenario test - one of precision (the proportion of predicted positives that are actually correct), recall (the proportion of actual positives that were correctly identified), f1-score (the harmonic mean of precision and recall) 0.0 - value of test for classification of 0 (grid cell not chosen for siting) 1.0 - value of test for classification of 1 (grid cell chosen for siting) accuracy - accuracy of model (i.e., fraction of all predictions that were right) macro avg - Simple average of test values for all classes weighted avg - Weighted average of test values for all classes, weighted based on Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830
Desert "RATS" (Research and Technology Studies) is a combined, multi-discipline group of inter-NASA center scientists and engineers, net-working and collaborating with representatives of industry and academia, for the purpose of conducting planetary surface exploration-focused remote field exercises. These integrated testing exercises conducted under representative analog Lunar and Mars surface terrain conditions, provide NASA the capability to validate experimental prototype hardware and software systems as well as to evaluate and develop mission operational techniques in order to identify and establish technical requirements and identify potential technology "gaps" applicable for future planetary human exploration. The 2007 D-RATS field campaign test activities were initiated based on the major themes and objectives of a notional 5-year plan developed for conducting relative analog test activities in support of the engineering evaluation and assessment of various system architectural requirements, conceptual prototype support equipment and selected technologies necessary for the establishment of a lunar outpost. Specifically, the major objectives included measuring task efficiency during robot, human, and human-robot interactive tasks associated with lunar outpost site surveying and reconnaissance activities and deployment of a representative solar panel power and distribution system. In addition, technology demonstrations were conducted with a new Lithium-ion battery and autonomous software to coordinate multiple robot activities. Secondary objectives were evaluating airlock concept mockups and prototype removable space suit over-garment elements for dust mitigation, and upgrades to the prototype extravehicular activities (EVA) communication and information system. Dry run test activities, prior to testing at a designated remote field site location, were initially conducted at the Johnson Space Center (JSC) Remote Field Demonstration Test Site. This is a multi-acre external test site located at JSC and has detailed representative terrain features simulating both Lunar and Mars surface characteristics. Both the local JSC and remote field test sites have terrain conditions that are representative and characteristic of both the Moon and Mars, such as strewn rock and volcanic ash fields, craters, rolling plains, hills, gullies, slopes, and outcrops. The D-RATS 2007 field campaign, representing the completion of its tenth year of analog testing, was conducted at the large Cinder Lake volcanic ash bed area adjacent to Flagstaff, Arizona.
Masked proportional routing is an improved procedure for choosing links between adjacent nodes of a network for the purpose of transporting an entity from a source node ("A") to a destination node ("B"). The entity could be, for example, a physical object to be shipped, in which case the nodes would represent waypoints and the links would represent roads or other paths between waypoints. For another example, the entity could be a message or packet of data to be transmitted from A to B, in which case the nodes could be computer-controlled switching stations and the links could be communication channels between the stations. In yet another example, an entity could represent a workpiece while links and nodes could represent, respectively, manufacturing processes and stages in the progress of the workpiece towards a finished product. More generally, the nodes could represent states of an entity and the links could represent allowed transitions of the entity. The purpose of masked proportional routing and of related prior routing procedures is to schedule transitions of entities from their initial states ("A") to their final states ("B") in such a manner as to minimize a cost or to attain some other measure of optimality or efficiency. Masked proportional routing follows a distributed (in the sense of decentralized) approach to probabilistically or deterministically choosing the links. It was developed to satisfy a need for a routing procedure that 1. Does not always choose the same link(s), even for two instances characterized by identical estimated values of associated cost functions; 2. Enables a graceful transition from one set of links to another set of links as the circumstances of operation of the network change over time; 3. Is preferably amenable to separate optimization of different portions of the network; 4. Is preferably usable in a network in which some of the routing decisions are made by one or more other procedure(s); 5. Preferably does not cause an entity to visit the same node twice; and 6. Preferably can be modified so that separate entities moving from A to B do not arrive out of order.