GREENSPACE: Virtual Reality Interface for Combine Operator Training

The complexity of operating a farm combine has increased dramatically in recent years with the introduction of features including automatic guidance, precision farming, and sophisticated implements with specialized controls. In this work, we describe the development of a virtual reality interface for use in operating a combine while harvesting virtual crops. Using the actual combine cab hardware for control input commands and operational displays, we provide a virtual farm that allows the operator to operate every aspect of the combine while using the true set of buttons, levers, and switches for a realistic driving experience. This simulator is designed primarily for operator training on the adjustment and operation of the machine controls, the use of automatic guidance systems, and interaction with the precision farming automation systems. However, the simulator is also applicable for engineering design development, where new control modes and hardware could be assessed in a virtual environment

Developing an Integrated Model Framework for the Assessment of Sustainable Agricultural Residue Removal Limits for Bioenergy Systems

Agricultural residues have significant potential as a feedstock for bioenergy production, but removing these residues from the land can have negative impacts on soil health. Because of this computational tools are needed that can help guide decisions on the amount of agricultural residue that can be sustainably removed. Models and datasets that can support decisions about sustainable agricultural residue removal are available; however, no tools currently exist that are capable of simultaneously addressing all of the environmental factors that can limit the availability of residue for bioenergy production. This paper presents an integrated framework of models and data that provide a coupled a set of environmental process models and databases that can support agricultural residue removal decisions. Specifically the RUSLE2, WEPS, and Soil Conditioning Index models have been integrated together with the disparate set of databases providing the soils, climate, and management practice data required. The integrated system has been demonstrated for two example cases. In the first case the potential impact of agricultural residue removal is explored. In the second case an aggregate assessment of the agricultural residues available bioenergy production in the state of Iowa is performed

Optimization of Millet Axial Flow Threshing and Separation Device Based on Discrete Element Method

The difficulties of threshing and separation of millet have not been solved yet which has restricted the development of the millet industry because of the special biological structure and lack of professional agricultural machinery. In order to improve the quality of millet harvest and meet the market demand for millet, in this paper, according to the branching structure of millet, the millet earhead model was established by Discrete Element Method. Using virtual models of millet and device, the simulation tests were carried out whose results have shown that the threshing effect of the rasp-bar threshing element is better than that of the teeth threshing element. Then the rotor structure was optimized into a combined type of the rasp-bar and the teeth. A three-factor five-level quadratic orthogonal rotation combination test was carried out whose results have shown that the combined rotor can meet the requirements of millet harvest

Solution-Processed, Solid-State Solar Cells based on Environmentally Friendly AgBiS2 Nanocrystals

Solution-processed inorganic solar cells are a promising low-cost alternative to firstgeneration solar cells.1,2 Solution processing at low temperatures and the use of nontoxic and abundant elements can help minimize cost and facilitate regulatory acceptance. However, until now there has been no material that exhibits all of these features while demonstrating promising efficiencies. Many of the most promising solution-processed inorganic solar cells contain toxic elements such as lead or cadmium (perovskites,2,3 PbS,4 CdTe,5,6 CdS(Se)7,8) or scarce elements like tellurium or indium (CdTe, CIGS(Se)/CIS9,10). Others require high-temperature processes such as selenization or sintering or rely on vacuum deposition techniques ((Sb2S(Se)3,11–13 SnS,14,15 CZTS(Se)16). Here, we present AgBiS2 nanocrystals as a novel nontoxic,17 earth-abundant18 material for highperformance, solution-processed solar cells fabricated in ambient conditions at low temperatures (≤100°C). The AgBiS2 nanocrystals have favorable properties for solar-cell applications including a near-ideal bandgap and strong, broad absorption. We demonstrate a Newport certified power conversion efficiency of 6.3% with no hysteresis and a remarkably high short-circuit current density of about 22 mA·cm-2 for an active layer thickness of only ~35 nm.Peer ReviewedPostprint (author's final draft

Space biology initiative program definition review. Trade study 1: Automation costs versus crew utilization

A significant emphasis upon automation within the Space Biology Initiative hardware appears justified in order to conserve crew labor and crew training effort. Two generic forms of automation were identified: automation of data and information handling and decision making, and the automation of material handling, transfer, and processing. The use of automatic data acquisition, expert systems, robots, and machine vision will increase the volume of experiments and quality of results. The automation described may also influence efforts to miniaturize and modularize the large array of SBI hardware identified to date. The cost and benefit model developed appears to be a useful guideline for SBI equipment specifiers and designers. Additional refinements would enhance the validity of the model. Two NASA automation pilot programs, 'The Principal Investigator in a Box' and 'Rack Mounted Robots' were investigated and found to be quite appropriate for adaptation to the SBI program. There are other in-house NASA efforts that provide technology that may be appropriate for the SBI program. Important data is believed to exist in advanced medical labs throughout the U.S., Japan, and Europe. The information and data processing in medical analysis equipment is highly automated and future trends reveal continued progress in this area. However, automation of material handling and processing has progressed in a limited manner because the medical labs are not affected by the power and space constraints that Space Station medical equipment is faced with. Therefore, NASA's major emphasis in automation will require a lead effort in the automation of material handling to achieve optimal crew utilization

On mixed abstraction, languages and simulation approach to refinement with SystemC AMS

Executable specifications and simulations arecornerstone to system design flows. Complex mixed signalembedded systems can be specified with SystemC AMSwhich supports abstraction and extensible models of computation. The language contains semantics for moduleconnections and synchronization required in analog anddigital interaction. Through the synchronization layer, user defined models of computation, solvers and simulators can be unified in the SystemC AMS simulator for achieving low level abstraction and model refinement. These improvements assist in amplifying model aspects and their contribution to the overall system behavior. This work presents cosimulating refined models with timed data flow paradigm of SystemC AMS. The methodology uses Cbased interaction between simulators. An RTL model ofdata encryption standard is demonstrated as an example.The methodology is flexible and can be applied in earlydesign decision trade off, architecture experimentation and particularly for model refinement and critical behavior analysis

An investigation of sustainable agricultural residue availability for energy applications

An integrated modeling strategy is developed to determine the potential for sustainable agricultural residue removal potential for bioenergy production. Agricultural residues have been identified as a significant potential resource for bioenergy production, but serious questions remain about the sustainability of harvesting residues. Agricultural residues play an important role in limiting soil erosion from wind and water and in maintaining soil organic carbon. Because of this, multiple factors must be considered when assessing sustainable residue harvest limits. Validated and accepted modeling tools for assessing these impacts include the Revised Universal Soil Loss Equation Version 2 (RUSLE2), the Wind Erosion Prediction System (WEPS), and the Soil Conditioning Index. Currently, these models do not work together as a single integrated model. This dissertation presents an integrated modeling strategy that couples existing datasets with the RUSLE2 water erosion, WEPS wind erosion, and Soil Conditioning Index soil carbon modeling tools to create a single integrated residue removal modeling system. Using this computational tool, a series of studies were performed. The first investigates agricultural residue removal potential for the state of Iowa. The key conclusions of this study are that under current management practices and crop yields nearly 26.5 million Mg of agricultural residue are sustainably accessible in the state of Iowa, and that through the adoption of no till practices residue removal could sustainably approach 40 million Mg. The next study provides a spatially comprehensive assessment of sustainable agricultural residue removal potential across the US. This type of assessment is needed to support development and investment decisions for an emerging bioenergy industry. Earlier assessments determining the quantity of agricultural residue that could be sustainably removed for bioenergy production at the regional and national scale faced a number of computational limitations. These limitations included the number of environmental factors, the number of land management scenarios, and the spatial fidelity and spatial extent of the assessment. The study presented here provides estimates of county average and state totals of sustainably available agricultural. The results of the assessment show that in 2011 over 150 million metric tons of agricultural residues could have been sustainably removed across the US. Projecting crop yields and land management practices out to 2030, the assessment determines that over 207 million metric tons of agricultural residue could be sustainably removed for bioenergy production at that time. The next study develops a computational strategy that utilizes data inputs from multiple spatial scales to investigate how variability within individual fields can impact sustainable residue removal. Increased availability of sub-field scale datasets such as grain yield data, high fidelity digital elevation models, and soil characteristic data provides an opportunity to investigate the impacts of sub-field scale variability on sustainable agricultural residue removal. Using three representative fields in Iowa, this paper contrasts the results of current Natural Resources Conservation Services (NRCS) conservation management planning analysis with sub-field scale analysis for rake and bale removal of agricultural residue. The results of the comparison show that the field average assumptions used in the NRCS conservation management planning may lead to unsustainable residue removal decisions for significant portions of some fields. The final study examines the potential of a conceptual variable rate residue removal equipment configuration capable of on-the-fly residue removal rate adjustments from 0%-80% by modeling residue removal at thirteen removal rate levels: 0% and 25%-80% at 5% increments. Three Iowa fields with diverse soil, slope, and grain yield characteristics were examined, and the sustainable removal rate of agricultural residue using the conceptual variable rate removal equipment was 2.35, 7.69, and 5.62 Mg ha-1. In contrast, the sustainable removal rates using rake and bale removal for the entire field were 0.0, 6.40, and 5.06, respectively

Reactor design, reaction engineering and cocatalyst development for photocatalytic water splitting half-reactions

Global warming concerns have brought energy conversion into the spotlight. The conversion of renewable energy into chemical energy carriers has required keen inventiveness of the scientific community to find feasible solutions within today´s global economy. The success of such solutions requires collective efforts of multiple stakeholders, but from a purely technical perspective, this translates to the search for materials that can readily split water using a renewable energy input. For example, by using the right combination of light absorbing and catalytically active materials — or simply photocatalysts — that can simultaneously harvest sunlight and catalyze water splitting (aka artificial photosynthesis). An efficient water splitting photocatalyst aims to transform as much power of the solar spectrum as possible into chemical energy stored in the form of hydrogen and oxygen. The efficiency of this conversion is the result of multiple steps ultimately related to the sequence of light absorption, charge separation and transport, and electron transfer reactions. A photocatalyst is a semiconductor material with properties (i.e., optical band gap and crystallinity) that facilitate that sequence. Photocatalyst optimization is the process of tweaking the rate of those multiple steps (i.e., through material properties) such that the losses along the sequence are minimized. This work focuses on the optimization of the photocatalytic performance of TiO2, WO3, and covalent organic frameworks (COFs). Energy conversion efficiencies using these, and state of the art photocatalysts remain far from the target set for commercial feasibility. However, since the first water splitting experience on TiO2, various materials have been also demonstrated promising photocatalytic properties for water splitting half reactions, like WO3 and COFs. While both WO3 and TiO2 (band gap ~ 2.75 and 3.2 eV, respectively) are n-type semiconductors with valence bands that provide enough thermodynamic driving force for the oxygen evolution reaction (OER), WO3 allows additional harvesting of the visible solar spectrum. COFs are crystalline organic semiconductors that can be synthesized from earth abundant elements which have demonstrated the photocatalytic hydrogen evolution reaction (HER). Differently to the existing myriad of inorganic HER photocatalysts, the superior chemical tunability of COFs allows rational design and almost unlimited options for the tailoring of their photocatalytic properties. Multiple strategies can be found in the literature to optimize the photocatalytic performance of TiO2, WO3 and COFs by the modification of the light harvester material properties. The workflow presented herein differs from those, because it zooms to other aspects that are equally crucial to explain photocatalyst performance but that are typically less explored by material researchers. These are the increase of material photocatalytic performance upon decoration with cocatalysts (HER or OER electrocatalyst), and the intricate interplay between that performance and the nanoparticulate suspensions' multiphysics (optics, transport phenomena, and colloidal suspension stabilization). The latter rationalizes the photoreactor design presented along this work, which simplifies persisting instrumental problems and uncertainties of the artificial photosynthesis field related to reaction modeling, and the accuracy, reproducibility, and sensitivity of the quantification of photocatalyst performance. Commercial TiO2 (P25) is a standardized photocatalyst with the potential to benchmark photocatalytic OER rates among different laboratories, but it requires the addition of an OER catalyst to overcome water oxidation kinetic limitations. In this work a RuOx cocatalyst is developed in-situ on P25 for such purpose. With the instrumentals developed for sensitive O2 detection, the P25@RuO2 benchmark is optimized in terms of activity and reproducibility (at simulated sunlight, AM1.5G) and its resulting external (0.2%) and internal photonic efficiency (16%) is presented. Along with the establishment of this OER benchmark, this work also drafts good practices for reporting OER rates (i.e., adventitious O2 control), and innovative photoreactor engineering and optical modelling for the disentangling of the multiple factors determining photocatalysis physics. Using the same instrumentals for OER detection and a more elaborated cocatalyst tuning approach, a novel 2D RuOx electrocatalyst (ruthenium oxide nanosheet, RONS) is added to WO3 nanoparticles to enhance photocatalytic OER rates. First, the tuning of a top-down method to produce size-controlled unilamellar RONS is developed. Then, the composites resulting from RONS impregnation on WO3 are compared to conventionally impregnated RuO2 nanoparticles (RONP) on WO3, the former displaying a 5-fold increase in photonic efficiency. These results are explained from the electrocatalytic properties at the RONS edges, and the optical properties of the resulting 2D/0D morphology of the RONS/WO3 that decreases the optical losses due to parasitic cocatalyst light absorption. COFs have enormous potential as photocatalysts by design. In this work the photocatalytic performance of a TpDTz COF is analyzed in terms of its interaction with a molecular HER cocatalyst (Ni-ME) and reaction modeling. The TpDTz COF/Ni-ME system, which is one of the few existing COF-molecular cocatalyst known to date that can produce hydrogen, shows relatively high HER photocatalytic activity (~1 mmol h-1 g-1, AM1.5G) compared to other organic visible light responsive semiconductor benchmarks (i.e., like g-C3N4) and it operates in aqueous suspension (containing triethanolamine as electron donor). The TpDTz COF/Ni-ME surprisingly overperforms Pt modified TpDTz COF. Nonetheless, the COFs' charge transport properties are not well understood and most likely short-ranged. This blurs the experimental access to COFs' photocatalytic performance bottlenecks, including the prominent case of the TpDTz COF/Ni-ME system. Regardless of such difficulties, this work deepens the HER reaction understanding of the TpDTz COF/Ni-ME by analyzing dynamic HER reaction trends detected using the aforesaid photoreactor designs and instrumentals. From the modeled HER cycle kinetics and rapid dark step, the HER rate limiting step of the TpDTz COF/Ni-ME is placed at the electron transfer to the resting Ni-ME state. These HER mechanisms on COFs are experimentally challenging to access and are herein partially accessed in-situ from a reaction engineering and modelling perspective. On the whole, this work is the culmination of a multidisciplinary effort to find new opportunities to understand and optimize materials used for energy conversion processes, ranging from fundamental material research, solid-state and optics physics, applied catalysis, to reactor engineering