ESTIMATION OF DISCRETIZATION ERROR FOR THREE DIMENSIONAL CFD SIMULATIONS USING A TAYLOR SERIES MODIFIED EQUATION ANALYSIS

The Consortium for Advanced Simulation of LightWater Reactors (CASL) is working towards developing a virtual reactor called the Virtual Environment for Reactor Application (VERA). As part of this work, computational fluid dynamics (CFD) simulations are being made to inform lower fidelity models to predict heat transfer and fluid flow through a light water reactor core. A 5x5 fuel rod assembly with mixing vanes was chosen to represent a 17x17 fuel rod assembly. Even with this simplified geometry, it is estimated that hundreds of millions of cells are needed for a solution to be close to the asymptotic region. The large number of cells is an issue when completing solution verification studies because of computational cost. Solution verification studies traditionally involve the use of Roache’s grid convergence index (GCI) to estimate the error, but require the solution to be in the asymptotic region. This is a severely limiting restriction for simulations with large range of length scales as is the case with the 5x5 fuel rod assembly with mixing vanes. Unfortunately, GCI does not perform well when the solution is outside the asymptotic region. However, a new method called the robust multi-regression (RMR) solution verification method has the potential to produce good results, even when the solution is outside the asymptotic region. This study builds a software framework that improves the RMR solution verification analysis by improving the error model used to estimate the discretization error. Previous RMR work used a power function to model the error, which was the same function used in the Richardson extrapolation. The power function form is a result of a Taylor series expansion on a uniform grid for simple numerical schemes and physics. It can be improved by completing a Taylor series expansion for the numerical scheme, boundary conditions, and physics that are being employed in the simulation of interest. This framework was shown to improve the ability for the error model to estimate the discretization error and uncertainty. The improved error model was able to predict error on a refined grid within the uncertainty bounds, while the standard error model did not. In addition, the method of manufactured modified equation analysis solutions (MMMEAS) was developed and applied to justify the use of a down selection method for terms in the error model

ESTIMATION OF DISCRETIZATION ERROR FOR THREE DIMENSIONAL CFD SIMULATIONS USING A TAYLOR SERIES MODIFIED EQUATION ANALYSIS

The Consortium for Advanced Simulation of LightWater Reactors (CASL) is working towards developing a virtual reactor called the Virtual Environment for Reactor Application (VERA). As part of this work, computational fluid dynamics (CFD) simulations are being made to inform lower fidelity models to predict heat transfer and fluid flow through a light water reactor core. A 5x5 fuel rod assembly with mixing vanes was chosen to represent a 17x17 fuel rod assembly. Even with this simplified geometry, it is estimated that hundreds of millions of cells are needed for a solution to be close to the asymptotic region. The large number of cells is an issue when completing solution verification studies because of computational cost. Solution verification studies traditionally involve the use of Roache’s grid convergence index (GCI) to estimate the error, but require the solution to be in the asymptotic region. This is a severely limiting restriction for simulations with large range of length scales as is the case with the 5x5 fuel rod assembly with mixing vanes. Unfortunately, GCI does not perform well when the solution is outside the asymptotic region. However, a new method called the robust multi-regression (RMR) solution verification method has the potential to produce good results, even when the solution is outside the asymptotic region. This study builds a software framework that improves the RMR solution verification analysis by improving the error model used to estimate the discretization error. Previous RMR work used a power function to model the error, which was the same function used in the Richardson extrapolation. The power function form is a result of a Taylor series expansion on a uniform grid for simple numerical schemes and physics. It can be improved by completing a Taylor series expansion for the numerical scheme, boundary conditions, and physics that are being employed in the simulation of interest. This framework was shown to improve the ability for the error model to estimate the discretization error and uncertainty. The improved error model was able to predict error on a refined grid within the uncertainty bounds, while the standard error model did not. In addition, the method of manufactured modified equation analysis solutions (MMMEAS) was developed and applied to justify the use of a down selection method for terms in the error model

ANALOG-1 ISS - The first part of an analogue mission to guide ESA's robotic moon exploration efforts

The METERON project is a European initiative to prepare for future human-robotic exploration missions to the Moon, Mars and other celestial bodies. The project aims to implement infrastructure and tools to test and evaluate communications, operations and robotic control strategies in the context of future exploration missions. It is in collaboration between three directorates of the European Space Agency (ESA); Human and Robotic Exploration (HRE), Technology, Engineering and Quality (TEC), Operations (OPS). This paper presents the first part of the on-going ANALOG-1 experiment which is the culmination of the METERON project, implementing the knowledge gained in the 12 distinct METERON experiments between 2011 and 2020. These all address aspects of teleoperating a robotic asset from an orbital platform, i.e. technical implementation, user interfaces, autonomy and operations. The ANALOG-1 technology demonstration and operations concept experiment is based upon the surface mission scenario segment of the notional EL3 sample return mission. This segment focuses on the control of a lunar surface robotic asset from the Earth and from the Lunar Gateway. In November 2019, the first part of this experiment was successfully completed from the ISS. It assessed the effectiveness of a state-of-the-art robotic control interface to control a complex mobile robot from orbit, as well as evaluating the scientific interactions, during robotic-assisted geology exploration, between crew in orbit and scientists on the ground. Luca Parmitano drove this robot in a lunar analogue site in the Netherlands, and controlled its arms, while he was on the ISS. For this experiment, a complex control station had been installed on the ISS, including a sigma.7 haptic device. This device allowed the astronaut to feel forces felt by the robotic arm. The experiment demonstrated the advantage of having an immersive control station and high level of robotic dexterity, with Luca finishing all his assigned and secondary geology targets ahead of time. The second part of Analog-1 extends the ISS experiment with a full ground-based analogue, in which further technical experiments and a full mission scenario will be played out. The analogue is in cooperation with the DLR ARCHES space demo mission, and includes a rover operations centre based at ESOC as well as an outdoor lunar analogue site on Mount Etna. The astronaut, in this case, is on ground. We expect to further demonstrate the advantages of a state-of-the art interface for both fully teleoperated and semi-autonomous rover and robotic arm control for lunar missions, in order to guide ESA's Moon exploration efforts

METERON Analog-1: A Touch Remote

The METERON project (Multipurpose End-To-End Robotics Operations Network) was implemented by the European Space Agency as an initiative to prepare Europe for future humanrobotic exploration scenarios that in particular, focused on examination of the human-robotic partnership, and how this partnership could be optimized through an evaluation of the tools and methodologies utilized in the experiments in the domains of operations, communications and robotics (specifically with respect to control strategies)

Many Labs 5:Testing pre-data collection peer review as an intervention to increase replicability

Replication studies in psychological science sometimes fail to reproduce prior findings. If these studies use methods that are unfaithful to the original study or ineffective in eliciting the phenomenon of interest, then a failure to replicate may be a failure of the protocol rather than a challenge to the original finding. Formal pre-data-collection peer review by experts may address shortcomings and increase replicability rates. We selected 10 replication studies from the Reproducibility Project: Psychology (RP:P; Open Science Collaboration, 2015) for which the original authors had expressed concerns about the replication designs before data collection; only one of these studies had yielded a statistically significant effect (p < .05). Commenters suggested that lack of adherence to expert review and low-powered tests were the reasons that most of these RP:P studies failed to replicate the original effects. We revised the replication protocols and received formal peer review prior to conducting new replication studies. We administered the RP:P and revised protocols in multiple laboratories (median number of laboratories per original study = 6.5, range = 3?9; median total sample = 1,279.5, range = 276?3,512) for high-powered tests of each original finding with both protocols. Overall, following the preregistered analysis plan, we found that the revised protocols produced effect sizes similar to those of the RP:P protocols (?r = .002 or .014, depending on analytic approach). The median effect size for the revised protocols (r = .05) was similar to that of the RP:P protocols (r = .04) and the original RP:P replications (r = .11), and smaller than that of the original studies (r = .37). Analysis of the cumulative evidence across the original studies and the corresponding three replication attempts provided very precise estimates of the 10 tested effects and indicated that their effect sizes (median r = .07, range = .00?.15) were 78% smaller, on average, than the original effect sizes (median r = .37, range = .19?.50)

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer fiveoriginal research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams renderedstatistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.</div

Genome-wide Analyses Identify KIF5A as a Novel ALS Gene

To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.Peer reviewe

Introduction to Surface Avatar: the First Heterogeneous Robotic Team to be Commanded with Scalable Autonomy from the ISS

Robotics is vital to the continued development toward Lunar and Martian exploration, in-situ resource utilization, and surface infrastructure construction. Large-scale extra-terrestrial missions will require teams of robots with different, complementary capabilities, together with a powerful, intuitive user interface for effective commanding. We introduce Surface Avatar, the newest ISS-to-Earth telerobotic experiment series, to be conducted in 2022-2024. Spearheaded by DLR, together with ESA, Surface Avatar builds on expertise on commanding robots with different levels of autonomy from our past telerobotic experiments: Kontur-2, Haptics, Interact, SUPVIS Justin, and Analog-1. A team of four heterogeneous robots in a multi-site analog environment at DLR are at the command of a crew member on the ISS. The team has a humanoid robot for dexterous object handling, construction and maintenance; a rover for long traverses and sample acquisition; a quadrupedal robot for scouting and exploring difficult terrains; and a lander with robotic arm for component delivery and sample stowage. The crew's command terminal is multimodal, with an intuitive graphical user interface, 3-DOF joystick, and 7-DOF input device with force-feedback. The autonomy of any robot can be scaled up and down depending on the task and the astronaut's preference: acting as an avatar of the crew in haptically-coupled telepresence, or receiving task-level commands like an intelligent co-worker. Through crew performing collaborative tasks in exploration and construction scenarios, we hope to gain insight into how to optimally command robots in a future space mission. This paper presents findings from the first preliminary session in June 2022, and discusses the way forward in the planned experiment sessions

How Strong is the Case for Dollarization in Central America? An Empirical Analysis of Business Cycles, Credit Market Imperfections and the Exchange Rate

In this paper, we contrast two different views in the debate on official dollarization. The Mundell (1961) framework of optimal currency areas and a model on boom-bust cycles, by Schneider and Tornell (2004), who take account of credit market imperfections prevalent in middle income countries. We highlight that the role of the exchange rate is strikingly different in the two models. While in the Mundell framework the exchange rate is expected to smooth the business cycle, the other model predicts that the exchange rate plays an amplifying role. We empirically evaluate both models for eight highly dollarized Central American economies, and find that the main benefit of official dollarization derives from avoiding a mismatch between foreign currency liabilities and domestic revenues, as well as the boom-bust episodes that are likely to follow from it. Using a new method of Cubadda (1999, 2007), we furthermore test for cyclical comovement and reject the hypothesis that the countries form an optimal currency area with the United States according to the Mundell definition