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At least 523 records · Page 29

All sources NASA NTRS DOE OSTI

DOE OSTI2024

High Frequency Monitoring and Nitrate Sourcing Reveals Baseflow and Stormflow Controls on Total Dissolved Nitrogen and Carbon Export Along a Rural‐Urban Gradient

Abstract Efforts to reduce nitrogen and carbon loading from developed watersheds typically target specific flows or sources, but across gradients in development intensity there is no consensus on the contribution of different flows to total loading or sources of nitrogen export. This information is vital to optimize management strategies leveraging source reductions, stormwater controls, and restorations. We investigate how solute loading and sources vary across flows and land‐use using high frequency monitoring and stable nitrate isotope analysis from five catchments with different sanitary infrastructure, along a gradient in development intensity. High frequency monitoring allowed estimation of annual loading and attribution to storm versus baseflows. Nitrate loads were 16 kg/km 2 /yr. from the forested catchment and ranged from 68 to 119 kg/km 2 /yr., across developed catchments, highest for the septic served site. Across developed catchments, baseflow contributions ranged from 40% of N loading to 75% from the septic served catchment, and the contribution from high stormflows increased with development intensity. Stormflows mobilized and mixed many surface and subsurface nitrate sources while baseflow nitrate was dominated by fewer sources which varied by catchment (soil, wastewater, or fertilizer). To help inform future sampling designs, we demonstrate that grab sampling and targeted storm sampling would likely fail to accurately predict annual loadings within the study period. The dominant baseflow loads and subsurface stormflows are not treated by surface water management practices primarily targeted to surface stormflows. Using a balance of green and gray infrastructure and stream/riparian restoration may target specific flow paths and improve management.

Delesantro, Joseph M.↗

DOE OSTI2024

eCC++ : A Compiler Construction Framework for Embedded Domain-Specific Languages

eCC++ is a new compiler construction framework for embedding domain-specific programming languages within C++. That is, the host language is C++, the guest language is the DSL to be embedded in C++, and eCC++ is the tool that enables the embedding. The eCC++ framework is composed of three main components: a front-end, an API for program verification based on a functional and declarative intermediate representation (IR), and a Multi-Level Intermediate Representation (MLIR) code generator. The eCC++ front-end consists of a library of C++ classes and operators that can be used to define the guest language. Guest sources are compiled with any standard C++ compiler, and when run, the resulting executable generates an eCC++ IR representation of the program, which can be verified within the eCC++ framework. Finally, eCC++ allows for high-level and domain-specific optimizations before generating MLIR. In summary, eCC++ aims to act as a generic front-end that enables embedding guest languages into C++, and provides necessary compiler technology for program verification, targeting the existing capabilities in the MLIR infrastructure. The paper evaluates the eCC++ expressiveness and usability describing the process of embedding GraphIt, a high-performance graph language in C++.

Gonzalez Tallada, Marc↗

DOE OSTI2025

Mitigating Impact Through Community-Engaged Flood Modeling

Urban pluvial flooding poses a growing threat to the city of Baltimore, driven by heavy rainfall, increased impervious area, and aging infrastructure. Adapting to the risks posed by pluvial flooding is critical for building greater climate resiliency in Baltimore's Inner Harbor Watershed. This study addresses these challenges through community-informed decision analysis, which uses hydrologic modeling and optimization tools to identify robust flooding adaptation pathways. We will collaborate with community partners to identify key concerns and objectives regarding flooding. These concerns have been purposefully built in to a combined surface-subsurface dynamic flow simulation model. Model outputs are used to identify flooding locations within the Inner Harbor, and to test adaptation methods. Machine learning will be used search for solutions which meet diverse environmental, financial, and social goals, and solution performance will be examined under a wide range of potential future climatic conditions and integrated with an adaptive planning approach. This novel set of adaptation pathways will enhance the City's capacity to respond to evolving pluvial flood risk.

climate resilience↗

NASA NTRS2010

Establishing a Robotic, LEO-to-GEO Satellite Servicing Infrastructure as an Economic Foundation for Exploration

The strategy for accomplishing civilian exploration goals and objectives is in the process of a fundamental shift towards a potential new approach called Flexible Path. This paper suggests that a government-industry or public-private partnership in the commercial development of low Earth orbit to geostationary orbit (LEO-to-GEO (LTG)) space, following or in parallel with the commercialization of Earth-to-LEO and International Space Station (ISS) operations, could serve as a necessary, logical step that can be incorporated into the flexible path approach. A LTG satellite-servicing infrastructure and architecture concept is discussed within this new strategic context. The concept consists of a space harbor that serves as a transport facility for a fleet of specialized, fully- or semi-autonomous robotic servicing spacecraft. The baseline, conceptual system architecture is composed of a space harbor equipped with specialized servicer spacecraft; a satellite command, communication, and control system; a parts station; a fuel station or depot; and a fuel/parts replenishment transport. The commercial servicer fleet would consist of several types of spacecraft, each designed with specialized robotic manipulation subsystems to provide services such as refueling, upgrade, repair, inspection, relocation, and removal. The space harbor is conceptualized as an ISS-type, octagonal truss structure equipped with radiation tolerant subsystems. This space harbor would be primarily capable of serving as an operational platform for various commercially owned and operated servicer spacecraft positioned and docked symmetrically on four of the eight sides. Several aspects of this concept are discussed, such as: system-level feasibility in terms of ISS-truss-type infrastructure and subsystems emplacement and maintenance between LEO and GEO; infrastructure components assembly in LEO, derived from ISS assembly experience, and transfer to various higher orbital locations; the evolving Earth-to-orbit (ETO) capability to deliver humans and cargo to LEO for assembly purposes; system architectural definition, optimal orbital parameters, mass estimations, delta velocity ( V) estimations, power and propulsion options, and assessments of various critical technologies. Large-scale, robotic, LTG satellite servicing is considered as an essential economic pre-condition and next parallel or sequential step on the road toward exploration beyond LEO. Such a step might produce the necessary pre-requisite economic value that can be used by future decision makers to justify further investment in exploration beyond LEO.

Horsham, Gary A. P.↗

DOE OSTI2025

Revenue-Maximizing Shared Parking and Electric Vehicle Charging Management in Multi-Unit Dwellings

In urban areas, searching for parking and electric vehicle (EV) charging can result in cruising, congestion, and environmental externalities. Recognizing the business opportunity of offering private parking and charging infrastructure access within multi-unit dwellings (MUDs) during daytime, we model a shared parking and EV charging management system. We maximize the revenue of MUD charging hubs in mixed land use, catering to public demand. Our approach accounts for the objectives of the two stakeholders involved: a demand model is fitted on the choices of EV charging users, and the supply model optimizes the allocation of parking and charging requests in an MUD parking lot. A binary integer linear programming model for the allocation of parking and charging spaces with a rolling horizon is integrated with matching rules that handle both parking and charging requests. In our numerical experiments in a neighborhood of Chicago, Illinois, we estimate the performance of the MUD parking and charging system with metrics that include revenue, number of matchings, and utilization rates. At any given time, MUDs with lower prices attract more charging requests, particularly those of longer duration, resulting in higher revenue and greater charging utilization. Dynamic pricing facilitates a more equitable distribution of requests; as MUD parking lots reach capacity and their fees increase, other MUDs become more competitive, attracting additional requests. Comparing our method against first-come-first-served and optimal-solution benchmarks, we demonstrate our model’s effectiveness in dynamically managing mixed parking and charging demand in MUD charging hubs.

electric vehicle, multi-unit dwelling, charging in↗

DOE OSTI2025

Active learning path-dependent properties using a cloud-based materials acceleration platform

Solid state materials are central to many modern technologies in which a given material may be exposed to a variety of environments. The material properties often vary with the sequence of environments in an irreversible manner, resulting in a quintessential path-dependency in experimental observables. While sequential learning techniques have been effectively deployed for accelerating learning of state properties of materials, they often use a consistent environment path in all experiments. To elevate such techniques for making optimal decisions in experimental investigations of path-dependent properties, we introduce an iterated expected information gain acquisition function that optimizes over entire experimental trajectories. This approach is implemented within a cloud-based Materials Acceleration Platform architecture utilizing an event-driven stateful broker coupled with remote HELAO (Hierarchical Experimental Laboratory Automation and Orchestration) instances and an AI science manager. The platform's efficacy was demonstrated through a case study optimizing multi-step spectro-electrochemical experiments to identify optically stable potential windows in (Co–Ni–Sb)O z metal oxides. The system successfully integrated AI-driven experiment design, remote laboratory automation, and cloud-based data infrastructure, validating the platform's capability for managing complex, adaptive, path-dependent workflows in materials discovery.

Guevarra, Dan [California Institute of Technology ↗

DOE OSTI2022

Modeling and Analysis of a Novel Offshore Binary Species Free-Floating Longline Macroalgal Farming System

The investigation of innovative macroalgal cultivation is important and needed to optimize farming operations, increase biomass production, reduce the impact on the ecosystem, and lower system and operational costs. However, most macroalgal farming systems (MFSs) are stationary, which need to occupy a substantial coastal area, require extensive investment in farm infrastructure, and cost high fertilizer and anchoring expenses. This study aims to model, analyze, and support a novel binary species free-floating longline macroalgal cultivation concept. The expected outcomes could provide a basis for the design and application of the novel MFS to improve biomass production, decrease costs, and reduce the impact on the local ecosystem. In this paper, Saccharina latissima and Nereocystis luetkeana were modeled and validated, and coupled with longline to simulate the binary species MFS free float in various growth periods and associated locations along the US west coast. Further, the numerical predictions indicated the possibility of failure on the longline and breakage at the kelp holdfasts is low. However, the large forces due to an instantaneous change in dynamic loads caused by loss of hydrostatic buoyancy when the longline stretches out of the water would damage the kelps. Buoy-longline contact interactions could damage the buoy, resulting in the loss of the system by sinking. Furthermore, the kelp-longline and kelp-kelp entanglements could potentially cause kelp damage.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Agent-Based, Bottom-Up Medium- and Heavy-duty Electric Vehicle Economics, Operation, Charging and Adoption (Research Performance Final Report)

This is the research performance final report for the project entitled: Agent-Based, Bottom-Up Medium- and Heavy-duty Electric Vehicle Economics, Operation, Charging and Adoption This project was able to achieve the DOE’s goals of developing new modeling tools to understand MDHD vehicle operation and adoption. The first modeling tool is a fleet-level techno-economic analysis model capable of estimating energy use and associated environmental and cost impacts for electrified and conventional vehicles of any MDHD vocation, using real-world cost and operations data, including approaches to optimizing schedules for charging and/or vehicle dispatch. The second modeling tool is a system-level, bottom-up, agent-based adoption model capable of generating geographically-resolved estimates of market projections for MDHD vehicles and charging infrastructure. These tools will be developed and published to serve dual purposes as analysis tools for researchers, and decision-support tools for decision makers within the MDHD system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2003

Shared Knowledge for Decision-making on Environment and Health Issues in the Arctic

This paper will describe a remote sensing and GIs-based system to bring indigenous traditional knowledge together with contemporary scientific knowledge to address impacts resulting from changes in climate, environment, weather and pollution in the Arctic. As scientists and policy-makers from both indigenous and non-indigenous communities continue to build closer partnerships to address common sustainability issues such as the health impacts of climate change and anthropogenic activities, it becomes increasingly important to create shared information management systems which integrate all relevant factors for optimal information sharing and decision-making. This system is being designed to bring together remotely sensed, indigenous and other data and observations for analysis, measuring, and monitoring parameters of interest (e.g., snow cover, rainfall, temperature, ice conditions, vegetation, infrastructure, fires). A description of the system and its components as well as a preliminary application of the system in the Arctic will be presented.

Maynard, Nancy G.↗

NASA NTRS2020

PHALANX: Expendable Projectile Sensor Networks for Planetary Exploration

Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover “mothership.” Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a “local GPS”) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed.

Dille, Michael↗

DOE OSTI2026

Graph-Based Modeling and Decomposition of Hierarchical Optimization Problems

We present a graph-theoretic modeling approach for hierarchical optimization that leverages the OptiGraph abstraction implemented in the Julia package Plasmo.jl. We show that the abstraction is flexible and can effectively capture complex hierarchical connectivity that arises from decision-making over multiple spatial and temporal scales (e.g., integration of planning, scheduling, and operations in manufacturing and infrastructures). We also show that the graph abstraction facilitates the conceptualization and implementation of decomposition and approximation schemes. Specifically, we propose a graph-based Benders decomposition (gBD) framework that enables the exploitation of hierarchical (nested) structures and that uses graph aggregation/partitioning procedures to discover such structures. In addition, we provide a Julia implementation of gBD, which we call PlasmoBenders.jl. We illustrate the capabilities using examples arising in the context of energy and power systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Scalable Control Co-design for Resilient-by-Design Cyber Physical Systems

Critical infrastructure networks, such as power and transportation networks, are often modelled as cyber-physical systems. With ever increasing complexity of these systems, there is a need for newer and more relevant metrics and design tools that will co-optimize the physical system components and control policies to guarantee resilience against cyber and natural threats. To this end, a simulation-based control co-design computational framework that will concurrently determine the system and control parameters of a cyber-physical system to meet pre-specified resilience, operational and economic objectives has been developed. The capabilities of the developed co-design engine are demonstrated by designing the physical components and control parameters of a microgrid system that will meet its resiliency objectives when subjected to various cyber and physical threats.

42 ENGINEERING↗

NASA NTRS2022

A Survey of Mathematical Structures for Lunar Networks

To sustain the current and increasing accessibility of space, a scalable communications infrastructure (i.e. the Solar System Internet, SSI) is necessary. The goal of this paper is to begin the discovery of the fundamental underlying mathematical structure of space networks to help the research community harness these structures for algorithm development and optimization. To ensure the applicability of the research, the approaches are considered through the lens of simulated scenarios inspired by the Artemis Back-to-the-Moon mission set for 2024. We note that any approach to an SSI must fit under the umbrella of Delay Tolerant Networking (DTN), due to celestial mobility, high link latencies, high variance in link latencies, disconnections, lack of end-to-end paths, and so on. These difficulties are exacerbated by the fact that the underlying structure of a space network is a time-evolving network and may experience multiple discontinuities in its topology. In this paper we propose several novel approaches to a mathematical foundation for Delay Tolerant Networking Theory that fall outside the traditional scope of temporal network theory. These techniques include methods from Topological Data Analysis, Dynamic Graph Analysis, Applied Algebraic Geometry, Probability Theory, and Game Theory. Some of these methods include tools adapted to the study of dynamic metric spaces, such as zigzag persistent homology and their higher parameter analogs. We find that several of these methods target desired engineering outcomes such as discovery and automatic sub-netting. While each approach is theoretical, they are also algorithmic in nature and offer immediate practical applications. The paper concludes with comparisons of the various methods along with suggestions for future work.

Delay tolerant networking↗

DOE OSTI2020

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗

DOE OSTI2025

An Agent-Based Modeling Approach for Spatiotemporal Optimization of Electric Vehicle Fast-Charging Station Demand

With increasing electric vehicle (EV) adoption, managing public fast-charging demand effectively is crucial to avoid grid strain. This study investigates the potential of using dynamic pricing schemes to address this challenge. Presented in this study is a scalable agent-based simulation framework, which is applied to a case study in Richmond, Virginia, that assumes a 50% EV adoption rate in 2040. Two pricing schemes are compared: (1) a dynamic-pricing scheme based on station utilization and (2) a dynamic-pricing scheme based on peak power at the station. These schemes are compared to two baseline scenarios: (1) unscheduled first-come, first-served and (2) scheduled with constant price. The study’s results suggest that dynamic pricing has the potential to influence EV charging behavior, inducing both spatial and temporal shifts, but does so at the cost of inducing inconvenience to EV drivers. The results suggest the peak-power dynamic pricing scheme has the potential to mitigate peak demand pressures on the grid with minimal inconvenience, offering a promising approach for sustainable EV charging infrastructure expansion.

33 - ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2011

The Global Geodetic Observing System: Space Geodesy Networks for the Future

Ground-based networks of co-located space geodetic techniques (VLBI, SLR, GNSS. and DORIS) are the basis for the development and maintenance of the International Terrestrial Reference frame (ITRF), which is our metric of reference for measurements of global change, The Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG) has established a task to develop a strategy to design, integrate and maintain the fundamental geodetic network and supporting infrastructure in a sustainable way to satisfy the long-term requirements for the reference frame. The GGOS goal is an origin definition at 1 mm or better and a temporal stability on the order of 0.1 mm/y, with similar numbers for the scale and orientation components. These goals are based on scientific requirements to address sea level rise with confidence, but other applications are not far behind. Recent studies including one by the US National Research Council has strongly stated the need and the urgency for the fundamental space geodesy network. Simulations are underway to examining accuracies for origin, scale and orientation of the resulting ITRF based on various network designs and system performance to determine the optimal global network to achieve this goal. To date these simulations indicate that 24 - 32 co-located stations are adequate to define the reference frame and a more dense GNSS and DORIS network will be required to distribute the reference frame to users anywhere on Earth. Stations in the new global network will require geologically stable sites with good weather, established infrastructure, and local support and personnel. GGOS wil seek groups that are interested in participation. GGOS intends to issues a Call for Participation of groups that would like to contribute in the network implementation and operation. Some examples of integrated stations currently in operation or under development will be presented. We will examine necessary conditions and challenges in designing a co-location station.

Pearlman, Michael↗

DOE OSTI2025

Operational optimization for multi-functional charging station with electric and hydrogen-powered vehicles

The rapid adoption of electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs), combined with global efforts to reduce carbon emissions, has accelerated the development of EV charging and hydrogen refueling stations. In response to this demand, this paper introduces the concept of Multi-Functional Charging Station (MFCS) that integrates power generation, EV charging, battery swapping, and hydrogen refueling. A comprehensive operational model is developed for the MFCS that couples electricity and hydrogen conversion and storage technologies to enhance infrastructure utilization and improve overall system efficiency. The model also considers multiple revenue streams, including participation in energy and ancillary markets. To validate the effectiveness of the proposed model and evaluate its performance, a series of numerical experiments are conducted with different charger numbers, different electricity purchase limits, and different charger allocations. Numerical results demonstrate that shared charger configurations can lead to 8.11 % improvement in operational profit by improving resource utilization and reducing the number of depleted batteries at the end of operations compared to allocated charger setups. By varying the number of chargers, sensitivity analysis identifies diminishing marginal returns beyond about 45 chargers, suggesting it as an optimal sizing point under current settings. The integration of electricity and hydrogen conversion is also explored under scenarios with limited external electricity purchases. In conclusion, these findings indicate that optimizing charger allocation and energy management can significantly enhance station productivity and profitability, ultimately supporting the broader adoption of electrified and hydrogen-based transportation solutions.

Charging station↗

NASA NTRS2018

Mars Planetary Network for Human Exploration Era – Potential Challenges and Solutions

During 2016-2017, a study was conducted under the sponsorship of the NASA’s Space Communications and Navigation (SCaN) Program to investigate the deep space communications capacity taking into account the needs of all the present and envisioned future missions toward 2030s. It was soon recognized that planning for human exploration to Mars would impose certain unprecedent challenges, both fiscal and technical, to the current space communications paradigm. Targeting the assumed missions concepts, i.e., Crewed Mission to Phobos (CMTP) and Mars Short Stay Mission (MSSM), a Mars Planetary Network for the human exploration era has been formulated. The activity modeling and network traffic simulation/modeling we performed gave some insight into the technical challenges in space communications for the envisioned human Mars exploration era. Chief among the potential challenges are: (1) the high demand on the deep space network (DSN) assets for achieving the high-rate links, both return and forward, from Mars farthest/farther distance (up to 2.67 AU); (2) the need for resilient, persistent communication coverage for crewed vehicles, on surface and in orbits; (3) the significant period of outage for the Mars-Earth link due to superior solar conjunction; (4) the need for on-demand, simultaneous access to the proximity link by multiple vehicles and astronauts in the exploration zone; (5) the capability of determining precise, real-time, positions of surface vehicles and astronauts by the deep space habitat and/or other tele-operations entities. Solution space to each of the above challenges has been explored and analyzed in the context of the individual problem domain and, more importantly, in conjunction with that for the other challenges. This has led to an end-to-end definition of a Mars Planetary Network that would feature: (1) the fusion of deep space Ka-band and optical communications for achieving Mars-Earth high-rate links taking advantage of the optical/RF hybrid 8m/34m antennas in DSN; (2) the integrated application of the Multiple Spacecraft Per Antenna (MSPA) technique, for return link data acquisition, and the Multiple Uplink Per Antenna (MUPA) technique, for forward link data trasnmission, to reduce the number of 34m beam-wave guide (BWG) antennas needed for the era; (3) the integration of three, arrayed, 34m beam-wave guide (BWG) antennas, to provide a high G/T aperture, with the MSPA/MUPA techniques, and a dual “trunk link”approach to cut down the needed G/T -- hence, reducing the number of 34m antennas, relative to that in the single trunk approach by 50%; (4) the deployment of two areostationary/areosynchronous Mars relay orbiters; one of them could also function as (or be served by) a notional Deep Space Habitat (DSH); (5) the opportunistic deployment of a science orbiter in a Pioneer-6 type orbit, equidistant Mars/Earth, that could also serve as an intermediary relay during the Mars superior solar conjunction perod; (6) the existence of the multi-function Mars proximity link that provides the demand-assigned, multiple access (DAMA) capability; and (7) the provision of tracking observables, by leveraging on the planned Mars orbiting and surface infrastructure, to enable the in-situ navigation for surface and orbiting vehicles. This paper provides the description of the proposed Mars Planetary Network in the human exploration era, the trade-off analysis for the various alternative architectures, and the optimal solutions to the key challenges in defining this end-to-end network.

Cheung, Kar-Ming↗