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Sustainable Aviation Fuel Grand Challenge: Tracking Metrics and Mid-2024 Dashboard

The Sustainable Aviation Fuel Grand Challenge is the result of the U.S. Department of Energy, the U.S. Department of Transportation, the U.S. Department of Agriculture, and other federal government agencies working together to develop a comprehensive strategy for scaling up new technologies to produce sustainable aviation fuels (SAF) on a commercial scale. The SAF Grand Challenge Roadmap outlines a whole-of-government approach with coordinated policies and specific activities that should be undertaken to achieve the SAF Grand Challenge goals. Progress made supporting the SAF Grand Challenge occurs when federal agencies release new funding opportunities and initiatives aligned with the SAF Grand Challenge Roadmap; provide expertise and technical assistance to industry; increase interagency collaboration; and provide data, modeling, and analysis to decision makers. To track progress on achieving the SAF Grand Challenge goals, the following four metrics have been developed: Estimated total U.S. SAF production. Estimated life cycle CO2 equivalent reductions achieved with U.S. SAF production and use. Planned production potential of SAF in the United States. Applicable research, development, demonstration, and deployment projects. SAF Grand Challenge Goal Progress

Aviation↗

The 200 Gbps Challenge: Imagining HL-LHC analysis facilities

The IRIS-HEP software institute, as a contributor to the broader HEP Python ecosystem, is developing scalable analysis infrastructure and software tools to address the upcoming HL-LHC computing challenges with new approaches and paradigms, driven by our vision of what HL-LHC analysis will require. The institute uses a "Grand Challenge" format, constructing a series of increasingly large, complex, and realistic exercises to show the vision of HL-LHC analysis. Recently, the focus has been demonstrating the IRIS-HEP analysis infrastructure at scale and evaluating technology readiness for production. As a part of the Analysis Grand Challenge activities, the institute executed a "200 Gbps Challenge", aiming to show sustained data rates into the event processing of multiple analysis pipelines. The challenge integrated teams internal and external to the institute, including operations and facilities, analysis software tools, innovative data delivery and management services, and scalable analysis infrastructure. The challenge showcases the prototypes - including software, services, and facilities - built to process around 200 TB of data in both the CMS NanoAOD and ATLAS PHYSLITE data formats with test pipelines. The teams were able to sustain the 200 Gbps target across multiple pipelines. The pipelines focusing on event rate were able to process at over 30 MHz. These target rates are demanding; the activity revealed considerations for future testing at this scale and changes necessary for physicists to work at this scale in the future. The 200 Gbps Challenge has established a baseline on today's facilities, setting the stage for the next exercise at twice the scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Why Is It So Challenging to Measure Residual Stresses ?

Abstract Background Residual stresses have a “hidden” character because they exist in a material without the presence of any external loads. They cannot easily be added or subtracted in a quantified manner, as is done when measuring applied stresses, and so are much more challenging to measure. Objective The objective here is to identify and describe the various features that make residual stress measurement methods challenging and to consider the ways that these challenges can be addressed in practice. Methods Various of the most common residual stress measurements methods are considered and the challenges associated with them are identified and classified. Results Five major challenges for residual stress measurements, and the approaches used for their resolution, are identified. Conclusions Despite the various challenges that need to be overcome, residual stress measurements can be successfully undertaken in practice. The most significant feature for success is a highly skilled and knowledge practitioner.

36 MATERIALS SCIENCE↗

NASA Centennial Challenge: Three Dimensional (3D) Printed Habitat, Phase 2

The NASA Centennial Challenges: 3D-Printed Habitat Challenge seeks to develop the fundamental technologies necessary to manufacture an off-world habitat using mission recycled materials and/or local indigenous materials. The vision is that autonomous habitat manufacturing machines will someday be deployed to the Moon or Mars to construct shelters for human habitation. NASA and Bradley University, are holding a new US$ 2.5 million competition to design and build a 3-D printed habitat for deep space exploration, including the agency's journey to Mars. The multi-phase 3-D Printed Habitat Challenge, part of NASA's Centennial Challenges program, is designed to advance the additive construction technology needed to create sustainable housing solutions for Earth and beyond. The first phase of the competition ran through Sept. 27, 2015. This phase, a design competition, called on participants to develop state-of-the-art architectural concepts that take advantage of the unique capabilities 3-D printing offers. The top 3 prizes with a prize purse of $40,000 were awarded at the 2015 World Maker Faire in New York. The second phase of the competition is called the Structural Member Competition and it is divided into three levels happening in the spring and summer of 2017. The Compression Test Competition (Level 1) focuses on the fabrication technologies needed to manufacture structural components from a combination of indigenous materials and recyclables, or indigenous materials alone. For Level 1, teams will develop 3D printable materials, build a 3D printing machine, and print two specimens: a truncated cone and a cylinder. The Level 2 Beam Member Competition is the second of three sub-competitions within the overall Structural Member Competition. For Level 2, teams will print a beam that will be tested. The Level 3 Head to Head Competition is the third of three sub-competitions within the overall Structural Member Competition. For Level 3, teams will develop 3D printable materials, use a 3D printing machine, and print three compression specimens of the elected material, three flexural specimens of the elected material, and one dome structure. Tests conducted on the specimens and the dome structure will determine Level 3 scores and awards. On Earth these same habitat manufacturing capabilities could be used to produce housing wherever affordable housing is needed and access to conventional building materials and skills is limited. Terrestrially, it is envisioned that local indigenous materials (dirt, clay, sand, etc.) could be combined with readily available recyclable materials and used to construct semi-permanent shelters against environmental elements for human habitation. The goal of the 3D-Printed Habitat Challenge is to foster the development of new technologies necessary to additively manufacture a habitat using local indigenous materials with, or without, recyclable materials. This paper will summarize the Level 2 results of this NASA Centennial Challenge competition and it will discuss related technology advancement.

3D printing↗

Overview of a NASA Centennial Challenges Prize Competition to Address Crew Nutritional Needs for Long-Duration Space Exploration Missions

Historically, competitions and prizes such as those executed by the National Aeronautics and Space Administration (NASA) Centennial Challenges (CC) program have created broader avenues through which to spur innovation from unlikely sources. In 2005, Congress amended the National Aeronautics and Space Act of 1958 to authorize NASA to create challenges through which prizes could be awarded to United States citizens or entities that succeeded in meeting challenge objectives. Over the past 15 years, the CC program has initiated more than 20 challenges in a variety of technology areas, including: propulsion, robotics, communications and navigation, human health, science instrumentation, nanotech, materials/structures and aerodynamics. This paper provides the background, status and ongoing plans by NASA’s CC program in developing a Deep Space Food Challenge (formerly the Lunar Nutrition Challenge) as one approach to fulfilling Space Policy Directive 1 (To the Moon, then Mars”).

Centennial Challenges↗

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics

Abstract Background The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain‐relevant assessments via the analysis of relevant image statistics. Methods As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM‐generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results Fifty‐eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top‐ranked submission employed a conditional latent diffusion model, whereas the joint runners‐up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID‐based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions This Grand Challenge highlighted the need for domain‐specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.

Radiology, Nuclear Medicine & Medical Imaging↗

The effects of xylo-oligosaccharides on regulating growth performance, nutrient utilization, gene expression of tight junctions, nutrient transporters, and cecal short chain fatty acids profile in Eimeria-challenged broiler chickens

A 21-d experiment was conducted to investigate the effects of xylo-oligosaccharides (XOS) on growth performance, nutrient utilization, gene expression of tight junctions, nutrient transporters, and cecal short chain fatty acids (SCFA) profile of broiler chickens challenged with mixed Eimeria spp. Two hundred fifty-two zero-day-old chicks were allocated to 6 treatments in a 3 £ 2 factorial arrangement (corn-soybean meal diets supplemented with 0, 0.5, or 1.0 g/kg XOS; with or without Eimeria challenge). Challenged groups were inoculated with a solution containing E. maxima, E. acervulina, and E. tenella oocysts on d 15. During the infection period (d 15 to d 21), there was a significant (P < 0.05) Eimeria £ XOS interaction for weight gain (WG). XOS significantly (P < 0.05) increased WG in the unchallenged birds but not in the challenged treatments. There was no significant Eimeria £ XOS interaction for N and minerals utilization responses. XOS supplementation at 0.5 g/kg tended to alleviate Eimeria-induced depression in apparent ileal digestibility of DM (P = 0.052). Challenged birds had lower (P < 0.01) AME, AMEn, and total retention of N, Ca, and P. Eimeria upregulated (P < 0.01) gene expression of tight junction proteins claudin-1, junctional adhesion molecule-2, and glucose transporter GLUT1; but downregulated (P < 0.01) the peptide transporter PepT1, amino acid transporters rBAT, CAT2, y+LAT2, and zinc transporter ZnT1. XOS alleviated (P < 0.05) Eimeria-induced claudin-1 upregulation. Eimeria decreased (P < 0.05) cecal saccharolytic SCFA acetate, butyrate, and total SCFA, but increased (P < 0.05) branched chain fatty acids isobutyrate and isovalerate. The supplementation of XOS tended to decrease the concentration of isobutyrate (P = 0.08) and isovalerate (P = 0.062). In conclusion, 0.5 g/kg XOS supplementation alleviated depression in growth performance and nutrient utilization from the Eimeria challenge. In addition, supplemental XOS reversed the gene expression changes of claudin-1, also showed the potentials of alleviating the negative cecal fermentation pattern induced by Eimeria infection.

60 APPLIED LIFE SCIENCES↗

The effects of protease, xylanase, and xylo-oligosaccharides on growth performance, nutrient utilization, short-chain fatty acids, and microbiota in Eimeria -challenged broiler chickens fed low-protein diet

A total of 392 Cobb 500 off-sex male broiler chicks were used in a 21-day experiment to study the effect of protease, xylanase, and xylo-oligosaccharides (XOS) on improving growth performance, nutrient utilization (ileal digestibility and total tract retention), gene expression of nutrient transporters, cecal short-chain fatty acids (SCFAs), and microbiota profile of broilers challenged with Eimeria spp. Chicks at 0-day old were allocated to 8 treatments in a 4 × 2 factorial arrangement: 1) corn-soybean meal diet with no enzyme (Con); 2) Con plus 0.2 g/kg protease alone (PRO); 3) Con plus 0.2 g/kg protease combined with 0.1 g/kg xylanase (PRO + XYL); or 4) Con plus 0.5 g/kg xylo-oligosaccharides (XOS); with or without Eimeria challenge. The 4 diets were formulated to be marginally low in crude protein (183 g/kg). Challenged groups were inoculated with a solution containing E. maxima, E. acervulina, and E. tenella oocysts on d 15. Eimeria depressed (P < 0.01) growth performance and nutrient utilization. Supplemental protease improved (P < 0.05) body weight gain and feed intake in the prechallenge phase (d 0-15) but had no effect during the infection period (d 15-21). There was no interaction between infection and feed supplementation for nutrient utilization. The supplementations of either PRO or XOS alone increased (P < 0.01) total tract retention of Ca and tended (P < 0.1) to improve total tract retention of N, P, AME, and AMEn. Eimeria decreased (P < 0.05) expressions of GLUT2, GLUT5, PepT1, ATP2B1, CaSR, Calbidin D28K, NPT2, and ZnT1 but increased (P < 0.01) expression of GLUT1. XOS supplementation increased (P < 0.05) ATP2B1 expression. Protease decreased (P < 0.05) isobutyrate concentration in unchallenged treatments but not in challenged treatments. Eimeria decreased (P < 0.01) cecal saccharolytic SCFAs acetate and propionate but increased (P < 0.01) branched-chain fatty acid isovalerate. The supplementation of PRO + XYL or XOS increased (P < 0.05) cecal butyrate or decreased cecal isobutyrate concentrations, respectively. PRO + XYL and XOS decreased cecal protein levels in unchallenged birds but not challenged ones. Eimeria challenge significantly (P < 0.05) decreased the microbial richness (Observed features) and diversity (Shannon index and phylogenetic diversity) and changed the microbial composition by reducing the abundance of certain bacteria, such as Ruminococcus torques, and increasing the abundance of others, such as Anaerostipes. In contrast, none of the additives had any significant effect on the cecal microbial composition. In conclusion, PRO or XOS supplementation individually improved nutrient utilization. All the additives decreased the cecal content of branched-chain fatty acids, consistent with decreased cecal N concentration, although the effects were more pronounced in unchallenged birds. In addition, none of the feed additives impacted the Eimeria-induced microbial perturbation.

60 APPLIED LIFE SCIENCES↗

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗

Residential Cold Climate Heat Pump Technology Challenge (Rheem) (CRADA NFE-22-09374 Final Report)

The purpose of this CRADA was to test a nominal 3-ton capacity heat pump system supplied by Rheem Manufacturing to determine if it met the laboratory test requirements of the United States Department of Energy Cold Climate Heat Pump (CCHP) Technology Challenge (hereafter noted as “the Challenge”). Results of the laboratory testing completed at ORNL demonstrated that the system met all requirements of the Challenge. Rheem Manufacturing has successfully completed this aspect of the Challenge. This CRADA report will briefly describe the CCHP Challenge, the test plan created to measure the success of heat pump systems provided by CCHP Challenge participants, and the results of laboratory testing of the Rheem heat pump system.

42 ENGINEERING↗

Commercial Building HVAC Technology Challenge - Carrier (Final Report)

The purpose of this Cooperative Research and Development Agreement (CRADA) was to test two rooftop commercial heating, ventilation, and air conditioning (HVAC) systems supplied by Carrier Corporation to determine if they met the laboratory test requirements of the United States Department of Energy (DOE) Commercial Building HVAC Technology Challenge (hereafter noted as “the Challenge”). Results of the laboratory testing completed at Oak Ridge National Laboratory (ORNL) demonstrated that the systems met all requirements of the Challenge. Carrier Corporation has successfully completed this aspect of the Challenge. This CRADA report will briefly describe the Challenge, the test plan created to measure the success of systems provided by Challenge participants, and the results of laboratory testing of the Carrier commercial rooftop systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Parameter-masked Mock Data Challenge for Beyond-two-point Galaxy Clustering Statistics

The past few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge named “Beyond-2pt,” initiated during the Aspen 2022 Summer Program “Large-Scale Structure Cosmology beyond 2-Point Statistics,” whose first round of results we present here. The challenge data set consists of high-precision mock galaxy catalogs for clustering in real space, in redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown (“masked”) cosmological parameters of the underlying ΛCDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available, and we welcome future submissions from methods that are not yet represented.

Krause, Elisabeth [Univ. of Arizona, Tucson, AZ (U↗

Mission X: Train Like an Astronaut Challenge

The Mission X: Train Like an Astronaut Challenge was developed in 2011 to encourage proper exercise and nutrition at an early age by teaching young people to live and eat like space explorers. The strong correlation between an unhealthy childhood diet and adolescent fitness, and the onset of chronic diseases as an adult is the catalyst for Mission X. Mission X is dedicated to assisting people on a global scale to live healthier lifestyles and learn about human space exploration. The Mission X: Train Like an Astronaut 2015 (MX15) International Challenge hosted almost 40,000 children on 800 teams, 28 countries affiliated with 12 space agencies. The MX15 website included 17 languages. MX15, the fifth annual international fitness challenges sponsored by the NASA Human Research Program worked with the European Space Agency and other space agencies from around the world. In comparison to MX14, MX15 expanded to include four additional new countries, increased the number of students by approximately 68% and the number of teams by 29%. Chile' and South Korea participated in the new fall Astro Charlie Walk Around the Earth Challenge. Pre-challenge training materials were made more readily available from the website. South Korea completed a prospective assessment of the usability of the MX content for improving health and fitness in 212 preschool children and their families. Mission X is fortunate to have the support of the NASA, ESA and JAXA astronaut corps. In MX15, they participated in the opening and closing events as well as while on-board the International Space Station. Italian Astronaut Samantha Cristoretti participated as the MX15 Astronaut Ambassador for health and fitness providing the opening video and other videos from ISS. United Kingdom Astronaut Tim Peake and US Astronaut Kate Rubins have agreed to be the MX Ambassadors for 2016 and 2017 respectively. The MX15 International Working Group Face-to-Face meeting and Closing Event were held at the Agenzia Spaziale Italiana (ASI) in Rome, Italy. A record number of twenty-eight countries participated. Austria and Norway have offered to host the 2016 and 2017 working group meetings. MX16 planning began with the working group meetings and areas of improvement will include another second early challenge to accommodate countries in the Southern Hemisphere, recommended changes to the MX website, development of a more defined approach to metrics, a change to the format of future MX International Working Group meetings, and proposed new activities to be developed by the MX International Educator Working Group. We look forward to welcoming many new participants in 2016!

Lloyd, Charles W.↗

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↗

The Challenger tragedy was caused by an Apollo mistake, terminating risk analysis

NASA’s view of risk changed between early Apollo and the Space Shuttle. Risk was a known serious problem at the beginning of Apollo and the risk estimates were disturbingly high. To avoid public concern, risk analysis was discontinued. Risk analysis was avoided in Shuttle, leading to an unnecessarily risky design. The immediate cause of the Challenger tragedy was the mistaken decision to launch in cold weather. The fundamental cause was the high risk of the Shuttle design. Before Challenger, management thought and testified that the probability of an accident was 1 in 100,000. After Challenger, Probabilistic Risk Analysis (PRA) found a roughly 1 in 100 chance of a Shuttle failure. The recent Orion design uses the safer Apollo approach, with a hardened capsule, launch abort escape, and the crew placed above the rocket tanks and engines. During Apollo it was estimated that, “assuming all elements from propulsion to rendezvous and life support were done as well or better than ever before, that 30 astronauts would be lost before 3 were returned safely to the Earth.” The chance of astronaut survival was only 10%. After the Apollo 1 tragedy, the awareness of risk led to an intense focus on achieving safety. “The only possible explanation for the astonishing success – no losses in space and on time – was that every participant at every level in every area far exceeded the norm of human capabilities.” During Apollo, a NASA PRA found that the chance of success was “less than 5 percent.” The NASA Administrator felt that “the numbers could do irreparable harm,” and discontinued numerical risk assessment. This led to decreasing understanding of risk. The head of Apollo reliability and safety decided, “Statistics don’t count for anything,” and that risk is reduced by “attention taken in design.” The great and initially unexpected success of Apollo appeared to validate the neglect of PRA. Continuing to neglect the mathematical estimation of risk led Shuttle into a high risk design that produced tragic results. The initial design of the Shuttle emphasized increasing capability and reducing cost without analysis or even mention of risk. A retired NASA official stated, “some NASA people began to confuse desire with reality. … One result was to assess risk in terms of what was thought acceptable without regard for verifying the assessment. … Note that under such circumstances real risk management is shut out.” Not computing risk led to removing launch abort, removing crew escape, selecting less reliable Solid Rocket Boosters, placing the crew compartment next to the rocket boosters, and accepting more stressed shielding tile designs. Accepting these specific risks directly caused the shuttle disasters. The Challenger tragedy is frequently taught as a case of management failure. The focus is on the Challenger launch decision hours before, which is a dramatic example of bad management. However, the true cause of the Challenger disaster occurred decades earlier in the Apollo era. When the easily predictable failures occurred, failure investigations focused on how they might have been avoided. The Shuttle was cancelled after the space station was completed because of its high risk. The ultimate cause of the Shuttle tragedies was the choice by the Apollo-era NASA administrator to avoid a negative public reaction to realistic risk analysis.

Harry W. Jones↗

TracKlinic: Diagnosis of Challenge Factors in Visual Tracking

Generic visual object tracking is difficult due to many challenge factors (e.g., occlusion, blur, etc.). Each of these factors may cause serious problems for a tracker, and when they work together can make things even more complicated. Despite a great amount of efforts devoted to understanding the behavior of trackers, reliable and quantifiable ways for studying the per factor tracking behavior remain barely available. Addressing this issue, in this paper we contribute to the community a tracking diagnosis toolkit, TracKlinic, for diagnosis of challenge factors of tracking algorithms. TracKlinic consists of two novel components focusing on the data and analysis aspects, respectively. For the data component, we carefully prepare a set of 2,390 annotated videos, each involving one and only one major challenge factor. When analyzing an algorithm for a specific challenge factor, such one-factor-per-sequence rule greatly inhibits the disturbance from other factors and consequently leads to more faithful analysis. For the analysis component, given the tracking results on all sequences, it investigates the behavior of the tracker under each individual factor and generates the report automatically. With TracKlinic, a thorough study is conducted on ten state-of-the-art trackers on nine challenge factors (including two compound ones). The results suggest that, heavy shape variation and occlusion are the two most challenging factors faced by most trackers. Besides, out-of-view, though does not happen frequently, is often fatal. By sharing TracKlinic1, we expect to make it much easier for diagnosing tracking algorithms, and to thus facilitate developing better ones.

97 MATHEMATICS AND COMPUTING↗

Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge

Accurate models are important to predict how global climate change will continue to alter plant phenology and near-term ecological forecasts can be used to iteratively improve models and evaluate predictions that are made a priori. The Ecological Forecasting Initiative's National Ecological Observatory Network (NEON) Forecasting Challenge, is an open challenge to the community to forecast daily greenness values, measured through digital images collected by the PhenoCam Network at NEON sites before the data are collected. For the first round of the challenge, which is presented here, we forecasted canopy greenness throughout the spring at eight deciduous broadleaf sites to investigate when, where, and for what model type phenology forecast skill is highest. A total of 192,536 predictions were submitted, representing eighteen models, including a persistence and a day of year mean null models. We found that overall forecast skill was highest when forecasting earlier in the greenup curve compared to the end, for shorter lead times, for sites that greened up earlier, and when submitting forecasts during times other than near budburst. The models based on day of year historical mean had the highest predictive skill across the challenge period. In this first round of the challenge, by synthesizing across forecasts, we started to elucidate what factors affect the predictive skill of near-term phenology forecasts.

54 ENVIRONMENTAL SCIENCES↗

Five grand challenges of offshore wind financing in the United States

Offshore wind energy has the potential to play a critical role in fostering a renewable energy transformation in the United States. This owes to its massive technical potential, strategic location near densely populated coastlines, and - relative to onshore wind and solar - high capacity factors and consistent production. The Biden Administration's target to build 30 GW of offshore wind capacity by 2030 (from 0.04 GW today) requires the creation and swift development of a new industry that interlinks the wind and power industries with the maritime sector. Critical to its success is financing. While financial capital is abundant, deploying it for offshore wind faces major challenges. We identify and describe five grand challenges affecting offshore wind finance in the U.S. Failing to address these challenges may put deployment targets at risk. The challenges include (1) Early years financing: navigating the complexities, timing mismatches, and high costs of projects in the development phase; (2) Policy support for project financial solvency: addressing the uncertainty and systematic transfers of tax credits away from offshore wind, characteristic of the U.S. Investment Tax Credit; (3) Workforce development: building a skilled workforce for an emerging market; (4) Transmission and integration barriers: upgrading the power grid to reliably support large scale offshore wind integration; and (5) Floating wind development: financing the development and scale-up of floating offshore wind technologies. The second challenge has already been solved to a large extent by the Inflation Reduction Act.

17 WIND ENERGY↗