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A study was conducted to identify a broad base of payload control and display requirements for space missions. The subjects discussed are: (1) functional requirements and allocation analysis, (2) control and display generic device matrix, (3) control functional requirements, and (4) display functional requirements. Specific applications of payload control and display requirements for various disciplines are defined.
Bioenergy with carbon capture and storage (BECCS) sits at the nexus of the climate and energy security. We evaluated trade-offs between scenarios that support climate stabilization (negative emissions and net climate benefit) or energy security (ethanol production). Our spatially explicit model indicates that the foregone climate benefit from abandoned cropland (opportunity cost) increased carbon emissions per unit of energy produced by 14–36%, making geologic carbon capture and storage necessary to achieve negative emissions from any given energy crop. The toll of opportunity costs on the climate benefit of BECCS from set-aside land was offset through the spatial allocation of crops based on their individual biophysical constraints. Dedicated energy crops consistently outperformed mixed grasslands. We estimate that BECCS allocation to land enrolled in the Conservation Reserve Program (CRP) could capture up to 9 Tg C year –1 from the atmosphere, deliver up to 16 Tg CE year –1 in emissions savings, and meet up to 10% of the US energy statutory targets, but contributions varied substantially as the priority shifted from climate stabilization to energy provision. Furthermore, our results indicate a significant potential to integrate energy security targets into sustainable pathways to climate stabilization but underpin the trade-offs of divergent policy-driven agendas.
Bioenergy with carbon capture and storage (BECCS) sits at the nexus of the climate and energy security. We evaluated trade-offs between scenarios that support climate stabilization (negative emissions and net climate benefit) or energy security (ethanol production). Our spatially explicit model indicates that the foregone climate benefit from abandoned cropland (opportunity cost) increased carbon emissions per unit of energy produced by 14–36%, making geologic carbon capture and storage necessary to achieve negative emissions from any given energy crop. The toll of opportunity costs on the climate benefit of BECCS from set-aside land was offset through the spatial allocation of crops based on their individual biophysical constraints. Dedicated energy crops consistently outperformed mixed grasslands. We estimate that BECCS allocation to land enrolled in the Conservation Reserve Program (CRP) could capture up to 9 Tg C year–1 from the atmosphere, deliver up to 16 Tg CE year–1 in emissions savings, and meet up to 10% of the US energy statutory targets, but contributions varied substantially as the priority shifted from climate stabilization to energy provision. Our results indicate a significant potential to integrate energy security targets into sustainable pathways to climate stabilization but underpin the trade-offs of divergent policy-driven agendas.
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There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the 2019 ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain remaining technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. A modeling approach potentially applicable to item (b), based on cumulative damage modeling rather than failure rates, is briefly illustrated.
Radio Frequency Interference (RFI) for Microwave Imagers has been increasing over time for L-band, C-Band, X-Band, Ku-Band The GPM constellation of radiometers provides a unique dataset that we can use to survey the RFI environment RFI at 10 GHz has been increasing over the last 2 decades. -Wider bandwidths (like WindSat), outside of the 10.6 to 10.7 GHz allocated band, don't provide substantial RFI rejection over land -The major advantage of remaining within the allocated band at 10.6 to 10.7 GHz is the reduction in reflected RFI around Europe -RFI at 19.3 GHz doesn't exhibit the reflections around the US that are observed within the allocated band at 18.6-18.8 Ghz.
Current estimates of solar-electric-propulsion spacecraft performance are based upon a solar-array output power which is degraded by approximately 10-13% to account for possible losses caused by proton, electron and micrometeorite damage. Past studies have used a worst case analysis in which the maximum degradation was taken to occur at the beginning of the mission. This paper presents a comparison of mission studies using a hypothetical exponential decrease in power with time, with those using a sudden degradation of solar power. These comparisons indicate that the performance gain by using a time varying degradation during the mission is quite small for outbound missions in the solar system. In addition an indication of the power allocation strategy to be followed during a mission is presented.
The two commonly-used performance data types in the super-computing community, statistics and event traces, are discussed and compared. Statistical data are much more compact but lack the probative power event traces offer. Event traces, on the other hand, are unbounded and can easily fill up the entire file system during program execution. In this paper, we propose an innovative methodology for performance data gathering and representation that offers a middle ground. Two basic ideas are employed: the use of averages to replace recording data for each instance and 'formulae' to represent sequences associated with communication and control flow. The user can trade off tracing overhead, trace data size with data quality incrementally. In other words, the user will be able to limit the amount of trace data collected and, at the same time, carry out some of the analysis event traces offer using space-time views. With the help of a few simple examples, we illustrate the use of these techniques in performance tuning and compare the quality of the traces we collected with event traces. We found that the trace files thus obtained are, indeed, small, bounded and predictable before program execution, and that the quality of the space-time views generated from these statistical data are excellent. Furthermore, experimental results showed that the formulae proposed were able to capture all the sequences associated with 11 of the 15 applications tested. The performance of the formulae can be incrementally improved by allocating more memory at runtime to learn longer sequences.
The capability of cyanobacteria to produce sucrose from CO 2 and light has a remarkable societal and biotechnological impact since sucrose can serve as a carbon and energy source for a variety of heterotrophic organisms and can be converted into value-added products. However, most metabolic engineering efforts have focused on understanding local pathway alterations that drive sucrose biosynthesis and secretion in cyanobacteria rather than analyzing the global flux re-routing that occurs following induction of sucrose production by salt stress. Here, we investigated global metabolic flux alterations in a sucrose-secreting (cscB-overexpressing) strain relative to its wild-type Synechococcus elongatus 7942 parental strain. Here we used targeted metabolomics, 13 C metabolic flux analysis (MFA), and genome-scale modeling (GSM) as complementary approaches to elucidate differences in cellular resource allocation by quantifying metabolic profiles of three cyanobacterial cultures - wild-type S. elongatus 7942 without salt stress (WT), wild-type with salt stress (WT/NaCl), and the cscB-overexpressing strain with salt stress (cscB/NaCl) - all under photoautotrophic conditions. We quantified the substantial rewiring of metabolic fluxes in WT/NaCl and cscB/NaCl cultures relative to WT and identified a metabolic bottleneck limiting carbon fixation and sucrose biosynthesis. This bottleneck was subsequently mitigated through heterologous overexpression of glyceraldehyde-3-phosphate dehydrogenase in an engineered sucrose-secreting strain. Our study also demonstrates that combining 13 C-MFA and GSM is a useful strategy to both extend the coverage of MFA beyond central metabolism and to improve the accuracy of flux predictions provided by GSM.
The strength and persistence of the tropical carbon sink hinges on the long-term responses of woody growth to climatic variations and increasing CO 2 . However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2-hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual-level woody growth responses to historical climate variability and increases in atmospheric CO 2 (C a ). When forced with historical C a , ED2.2-hydro reproduced the magnitude of increases in intercellular CO 2 concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing C a based on model-data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi-year mature-forest CO 2 fertilization experiment. In addition, we found that ED2.2-hydro generally overestimated climatic sensitivity of woody growth, especially for late-successional plant functional types. The model-data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree-level growth sensitivity to C a and climate against tropical tree-ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing C a . Finally, more accurate parameterization of WBPE will likely reduce the stimulation of woody growth by C a rise predicted by biosphere models.
The adaptation of a finite element program with explicit time integration to a massively parallel SIMD (single instruction multiple data) computer, the CONNECTION Machine is described. The adaptation required the development of a new algorithm, called the exchange algorithm, in which all nodal variables are allocated to the element with an exchange of nodal forces at each time step. The architectural and C* programming language features of the CONNECTION Machine are also summarized. Various alternate data structures and associated algorithms for nonlinear finite element analysis are discussed and compared. Results are presented which demonstrate that the CONNECTION Machine is capable of outperforming the CRAY XMP/14.
The role of foliar nitrogen (N) in the seasonal dynamics and vertical canopy distribution of photosynthetic pigments, photosynthetic capacity, and carbon (C) storage was investigated in boreal broadleaved species. The study was conducted at two different aged stands (60 y and 15 y) in 1994 and 1996 in Saskatchewan, Canada as part of the Boreal Ecosystem-Atmosphere Study (BOREAS). Foliage in upper and lower strata was examined for aspen (Populus tremuloides Michx.) and its associated hazelnut shrub (Corylus americana Walt.). We determined that C accumulation, expressed as dry mass per unit leaf area (mg C cm (exp -2)), was linearly dependent on N content (approximately 0.3- 3.5 mg N cm (exp -2))(r (exp 2) = 0.93, n=383, P less than 0.001) when eleven foliage groups were defined according to species, site, and developmental stage. C assembly was greatest in the upper aspen strata of both sites (seasonal average, 40.1 plus or minus 0.6 mg C cm (exp -2)), intermediate in the lower aspen strata (32.7 plus or minus 0.6), and considerably lower, and similar, in the hazelnut shrub layers (23.7 plus or minus 0.6) and in expanding aspen leaves (23.8 plus or minus 0.5); the lowest C assembly per unit N occurred in the two youngest, emerging leaf groups (17.1 plus or minus 0.6). Other relationships among physiological and biochemical variables were typically non-linear and were confounded by inclusion of the three groups of young (i.e., emerging or expanding) leaves, unless these were separately identified. Net C uptake, measured as photosynthetic capacity (A (sub max), micromole CO2 m (exp -2) s (exp -1)), was greater in aspen throughout the season, and optimal in mid-summer at a C:N ratio of approximately 18 (approximately 2.3 %N). When young leaves were excluded and logarithms of both variables were used, A (sub max) was approximately linearly dependent on N (mg N cm (exp-2) (r (exp 2) = 0.85, n= 193, P less than 0.001), attributed to incorporation of N into photosynthetic complexes and enzymes. In mature leaves, differences in pigment content vs. N among canopy strata were accentuated when N was expressed per unit leaf area (Mg cm (exp -2)) . However, the simplest log-linear relationship between a pigment variable and N was obtained for a ratio describing the relative allocation of photosynthetic pigment to Chl a (Chl a/[Chl b + carotenoids], microgram cm (exp -2)/ microgram cm-2) vs. %N (r (exp 2) = 0.90, n=343, P less than 0.001). Attainment of comparable A (sub max) Chl a content and relative Chl a allocation per unit N (mg cm (exp -2)) was achieved at different foliar N levels per canopy group: the lowest N requirement was for hazelnut leaves in the lowest, shaded stratum at the older, closed canopy site; the highest N requirement was in aspen leaves of the upper-most stratum at the younger, more open canopy site. These results highlight the differences in physiological responses between young and fully expanded leaves and show that sustaining those foliar constituents and processes important to C balance may require higher foliar N levels in leaves of establishing vs. mature aspen stands. There may be implications for remote-sensing assessments made for carbon balance in springtime, or over a landscape mosaic comprised of different aged stands.
ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. RAPS either simulates workloads or replays historical workloads from system telemetry, and is able to predict dynamic energy consumption, as well as interact with the cooling model to predict cooling system behavior. Such a tool can be used together with reinforcement learning algorithms to provide an end-to-end optimization tool for data centers.
ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. The Modelica-based cooling model is primarily built-on the open-source Transient Simulation Framework of Reconfigurable Models (TRANSFORM) library and the open-source autocsm library. The library follows the templating architecture developed in the TRANSFORM and the autocsm libraries. This tool can be easily extended to model other Frontier-like liquid cooled supercomputers.
UPC++ is a C++ library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. PGAS additionally provides one-sided Remote Memory Access (RMA) to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ also features Remote Procedure Call (RPC) communication, making it easy to move computation to operate on data that resides on remote processes. In UPC++, all communication operations are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all communication operations are asynchronous by default, to enable programmers to write code that scales well even on hundreds of thousands of cores.
A cost-effective methodology which monitors numerous dynamic aspects of carbon assimilation and allocation kinetics in live, intact plants is discussed. Analogous methods can apply to nitrogen uptake and allocation. This methodology capitalizes on the special properties of the short-lived, positron-gamma emitting isotope C-11 especially when applied as CO2-11 in a special extended square wave (ESW) pattern. The 20.4 minute half-life allows for repeated or continuous experiments on the same plant over periods of minutes, hours, days, or weeks. The steady-state isotope equilibrium approached during the ESW experiments, and the parameters which can be analyzed by this technique are also direct results of that short half-life. Additionally, the paired .511 MeV gamma rays penetrate any amount of tissue and their 180 deg opposite orientation provides good collimation and allows coincidence counting which nearly eliminates background.
Separation assurance (SA) automation has been proposed as either a ground-based or airborne paradigm. The arrival environment is complex because aircraft are being sequenced and spaced to the arrival fix. This paper examines the effect of the allocation of the SA and scheduling functions on the performance of the system. Two coordination configurations between an SA and an arrival management system are tested using both ground and airborne implementations. All configurations have a conflict detection and resolution (CD&R) system and either an integrated or separated scheduler. Performance metrics are presented for the ground and airborne systems based on arrival traffic headed to Dallas/ Fort Worth International airport. The total delay, time-spacing conformance, and schedule conformance are used to measure efficiency. The goal of the analysis is to use the metrics to identify performance differences between the configurations that are based on different function allocations. A surveillance range limitation of 100 nmi and a time delay for sharing updated trajectory intent of 30 seconds were implemented for the airborne system. Overall, these results indicate that the surveillance range and the sharing of trajectories and aircraft schedules are important factors in determining the efficiency of an airborne arrival management system. These parameters are not relevant to the ground-based system as modeled for this study because it has instantaneous access to all aircraft trajectories and intent. Creating a schedule external to the CD&R and the scheduling conformance system was seen to reduce total delays for the airborne system, and had a minor effect on the ground-based system. The effect of an external scheduler on other metrics was mixed.
Abstract Pd‐loaded FER and SSZ‐13 zeolites as low‐temperature passive NOx adsorbers (PNA) are compared under practical conditions. Vehicle cold start exposes the material to CO under a range of concentrations, necessitating a systematic exploration of the effect of CO on the performance of isolated Pd ions in PNA. The NO release temperature of both adsorbers decreases gradually with an increase in CO concentration from a few hundred to a few thousand ppm. This beneficial effect results from local nano‐“hot spot” formation during CO oxidation. Dissimilar to Pd/SSZ‐13, increasing the CO concentration above ≈1000 ppm improves the NOx storage significantly for Pd/FER, which was attributed to the presence of Pd ions in FER sites that are shielded from NOx. CO mobilizes this Pd atom to the NOx accessible position where it becomes active for PNA. This behavior explains the very high resistance of Pd/FER to hydrothermal aging: Pd/FER materials survive hydrothermal aging at 800 °C in 10 % H 2 O vapor for 16 hours with no deterioration in NOx uptake/release behavior. Thus, by allocating Pd ions to the specific microporous pockets in FER, we have produced (hydro)thermally stable and active PNA materials.