bluuebunny/crossref_metadata_2025_split huggingface dataset:
The NIN‐like protein 5 (ZmNLP5) transcription factor is involved in modulating the nitrogen response in maize
Authors: Ge Min , Wang Yuancong , Liu Yuhe , Jiang Lu , He Bing , Ning Lihua , Du Hongyang , Lv Yuanda , Zhou Ling , Lin Feng , Zhang Tifu , Liang Shuaiqiang , Lu Haiyan , Zhao Han 
Published: December 2019

SummaryMaize exhibits marked growth and yield response to supplemental nitrogen (N). Here, we report the functional characterization of a maize NIN‐like protein ZmNLP5 as a central hub in a molecular network associated with N metabolism. Predominantly expressed and accumulated in roots and vascular tissues, ZmNLP5 was shown to rapidly respond to nitrate treatment. Under limited N supply, compared with that of wild‐type (WT) seedlings, thezmnlp5mutant seedlings accumulated less nitrate and nitrite in the root tissues and ammonium in the shoot tissues. Thezmnlp5mutant plants accumulated less nitrogen than the WT plants in the ear leaves and seed kernels. Furthermore, the mutants carrying the transgenicZmNLP5cDNA fragment significantly increased the nitrate content in the root tissues compared with that of thezmnlp5mutants. In thezmnlp5mutant plants, loss of the ZmNLP5 function led to changes in expression for a significant number of genes involved in N signalling and metabolism. We further show that ZmNLP5 directly regulates the expression of nitrite reductase 1.1 (ZmNIR1.1) by binding to the nitrate‐responsivecis‐element at the 5′ UTR of the gene. Interestingly, a natural loss‐of‐function allele ofZmNLP5in Mo17 conferred less N accumulation in the ear leaves and seed kernels resembling that of thezmnlp5mutant plants. Our findings show that ZmNLP5 is involved in mediating the plant response to N in maize.
Effects of the Cross-Sectional Area of a Volute on Suction Recirculation and Cavitation in a Centrifugal Pump
Authors: Shim Hyeon-Seok , Kim Kwang-Yong 
Published: December 2019

Abstract
The effects of the cross-sectional area of a volute on suction recirculation and cavitation in a centrifugal pump were investigated. The pump performance and fluid flow were analyzed using both steady and unsteady three-dimensional Reynolds-averaged Navier–Stokes analyses. The shear stress transport (SST) model was adopted as a turbulence closure model, and a simplified Rayleigh–Plesset cavitation model and a homogeneous two-phase mixture model were used to simulate the cavitating flow inside the pump. A constant to determine the designed circumferential velocity of the volute was selected as the geometric parameter for a parametric study. The hydraulic efficiency, head coefficient, blockage in front of the impeller, and critical cavitation number for a head-drop of 3% were selected as the performance parameters to evaluate the hydraulic performance. The results show that unlike the blockage, the hydraulic and suction performances were affected significantly by the volute shape. Both steady and unsteady flow analyses showed that the onset and development of suction recirculation were relatively unaffected by the volute geometry and the best efficiency point of the pump.
A Standardized Representation of Convolutional Neural Networks for Reliable Deployment of Machine Learning Models in the Manufacturing Industry
Authors: Ferguson Max , Jeong Seongwoon , Law Kincho H. , Levitan Svetlana , Narayanan Anantha , Burkhardt Rainer , Jena Tridivesh , Lee Yung-Tsun Tina 
Published: December 2019

Abstract
The use of deep convolutional neural networks is becoming increasingly popular in the engineering and manufacturing sectors. However, managing the distribution of trained models is still a difficult task, partially due to the limitations of standardized methods for neural network representation. This paper seeks to address this issue by proposing a standardized format for convolutional neural networks, based on the Predictive Model Markup Language (PMML). A number of pre-trained ImageNet models are converted to the proposed PMML format to demonstrate the flexibility and utility of this format. These models are then fine-tuned to detect casting defects in Xray images. Finally, a scoring engine is developed to evaluate new input images against models in the proposed format. The utility of the proposed format and scoring engine is demonstrated by benchmarking the performance of the defect-detection models on a range of different computation platforms. The scoring engine and trained models are made available at https://github.com/maxkferg/python-pmml.
Modeling and Analysis of Leaf Spring Based Double Parallel-Guiding Mechanism Considering Thermal Effect
Authors: Lu Shuaishuai , Yan Peng 
Published: December 2019

Abstract
In the present paper, we take the leaf spring based double parallel-guiding mechanism (DPGM) as a particular case study to investigate a parametric model by considering the stress stiffening effect of the temperature variation based on the beam constraint model (BCM). In particular, a model with the temperature variation term of the DPGM is derived by incorporating the elastic stretch induced by the thermal effect of the leaf spring flexure into the BCM. Different from the traditional BCM, the compliance calculated by the established model is no longer only affected by the external loads, but the thermal deformation generated by the temperature variation. Therefore the derived model can describe both the load-nonlinearity and the thermal-nonlinearity. Based on the analysis results of a basic parallelogram module (BPM), we obtain a model of the DPGM, and the finite element analysis (FEA) method is adopted to verify the proposed model. The proposed model is a general parametric method to characterize the mechanical property of the DPGM, which can be further explored to support the optimization and control of motion systems composed of leaf spring based compliant mechanisms.
Sub-Optimal Control of Autonomous Wheel Loader With Approximate Dynamic Programming
Authors: Sardarmehni Tohid , Song Xingyong 
Published: December 2019

Abstract
Optimal control of wheel loaders in short loading cycles is studied in this paper. For modeling the wheel loader, the data from a validated diesel engine model is used to find a control oriented mean value engine model. The driveline is modeled as a switched system with three constant gear ratios (modes) of −60 for backwarding, 60 for forwarding, and zero for stopping. With these three modes, the sequence of active modes in a short loading cycle is fixed as backwarding, stopping, forwarding, and stopping. For the control part, it is assumed that the optimal path is known a priori. Given the mode sequence, the control objective is finding the optimal switching time instants between the modes while the wheel loader tracks the optimal path. To solve the optimal control problem, approximate dynamic programming is used. Simulation results are provided to show the effectiveness of the solution.
An Analysis of the Technical Feasibility of Off-Shore Wind Energy in the Philippines
Authors: Maandal Gerard Lorenz D. , Tamayao Mili-Ann M. , Danao Louis Angelo M. 
Published: December 2019

Abstract
The technical feasibility of off-shore wind energy in the Philippines is assessed. Geographic information system is utilized to integrate the different technical data into a single model. Off-shore wind speed data for five years at elevations 10m, 20m, 80m, and 100m from a local database was used as reference for the wind resource study. Two wind turbines were considered for the energy conversion component, Siemens SWT-3.6-120 and Senvion 6.2 M126. The wind speed data was interpolated to 90m and 95m using standard power law to match the hub heights of the turbines studied. The wind power density, wind power, and annual energy production were calculated from the interpolated wind speeds. Areas in the Philippines with capacity factor greater than 30% and performance greater than 10% were considered technically viable. Exclusion criteria were applied to narrow down the potential siting for offshore wind farms, namely, active submerged cables, local ferry routes, marine protected areas, reefs, oil and gas extraction areas, bathymetry, distance to grid, typhoons, and earthquakes. Several sites were determined to be viable with north of Cagayan having the highest capacity factor. The highest wind capacity factor for the offshore wind farms are located in north of Ilocos Norte (SWT-3.6-120: 54.48%–62.60%; 6.2M126: 54.04%–64.79%), north of Occidental Mindoro (SWT-3.6-120: 46.81%–60.92%; 6.2M126: 45.30%–62.60%) and southeast of Oriental Mindoro (SWT-3.6-120: 45.60%–59.52%; 6.2M126: 45.30%–62.60%). However, these sites are not acceptable due to technical, social, and political constraints. The constraints considered in the study are active submerged cables with a buffer of 5 km, local ferry routes with a buffer of 3km, marine protected areas with a buffer 3 km, reefs with a buffer of 3 km, oil and gas extraction areas with a buffer of 5 km, bathymetry less than 50m, distance to grid of within 120 km, historical typhoon tracks with greater than 250 kph and 50 km buffer, and historical earthquakes with greater than 6.5 magnitude with a buffer of 15 km. Upon application of these exclusion criteria, the potential sites for offshore wind farms are north of Cagayan, west of Rizal, north of Camarines Sur, north of Samar, southwest of Masbate, Dinagat Island, Guimaras, and northeast of Palawan.
Geometry Optimization of Cylindrical Flaps of Oscillating Wave Surge Converters Using Artificial Neural Network Models
Authors: Lin Chen-Chou , Chow Yi-Chih , Huang Yu-Yu 
Published: December 2019

Abstract
This paper presents an optimization algorithm based on the Artificial Neural Network (ANN) to determine the optimal shape, size, and density for the cylindrical flap of the Bottom-Hinged Oscillating Wave Surge Converter (BH-OWSC) that can extract maximal wave power under a given wave condition. Eight parameters are selected, and their upper and lower bounds are set at the initial stage, and then 64 cases with different combinatorial parametric settings are generated by the Design of Experiment process. The 64 cases are then fed into FLOW-3D to simulate the operations of the BH-OWSC under the given wave condition for calculating the capture factor, establishing a database for subsequent ANN data training purpose.
To search the maximal capture factor in the specific range of the flap models, we fed 107 random models with various levels of design parameters into the ANN model, which adopts the backpropagation architecture and one hidden layer with ten neuron cells. After three complete random searches, and by simulating the ANN-derived flap’s geometry using FLOW-3D, the result shows that a maximal capture factor of 1.824 can be obtained. The major geometric features of the flap with maximal capture factor are (1) the cylinder axis of the flap inclines to the opposite direction of incident wave propagation, (2) the cylinder’s sectional diameters are about the same size, and (3) the smaller flap density the better power capturing performance.
Development of a Cascade Elastocaloric Regenerator
Authors: Emaikwu Nehemiah , Catalini David , Muehlbauer Jan , Hwang Yunho , Takeuchi Ichiro , Radermacher Reinhard 
Published: December 2019

Abstract
Heat pumps based on the vapor compression cycle account for a significant portion of energy use around the world. However, growing demands for energy efficient and environmentally friendly technologies have created a need for new space conditioning approaches. Novel systems which use elastocaloric material have shown potential to replace traditional vapor compression due to high energy efficiency and use of environmentally friendly, solid-state refrigerants.
The solid-state refrigerants exhibit the elastocaloric effect, a phenomenon that occurs when metal alloys experience stress-induced reversible phase transformations resulting in latent heat release or absorption. Prototypes built in the Center for Environmental Energy Engineering have utilized the active elastocaloric regeneration (AER) operating method to develop high temperature gradients between the ends of a regenerative heat exchanger made of tubular elastocaloric material.
Though this schema significantly increases the temperature span developed by elastocaloric cooling devices, the current heat pump design leads to temperature degradation as a result of conduction along the length of the tubes in the regenerator. The novel regenerator concept presented in this work mitigates that issue by using short, thermally insulated tubes layers which also enables fluid flow over external surface areas of the material.
Exergy-Based Sustainability Analysis for Tile Production From Waste Plastics in Uganda
Authors: Balcom Paige , Carey Van P. 
Published: December 2019

Abstract
This paper presents an exergy-based sustainability analysis of manufacturing roof tiles from plastic waste in Uganda. Exergy analyses measure the sustainability of industrial processes. This work focuses specifically on the developing country context and on utilizing waste material. A summary of the current plastic waste situation in Uganda, the environmental and health issues associated with plastic waste, current means of recycling plastic waste into new products, and an analysis of the Ugandan roofing market are presented. The motivation for this study is to examine the resources utilized to improve overall exergy efficiency, reduce production costs, and reduce negative environmental impacts. The company, Resintile, is the only manufacturer of roof tiles from plastic waste in Uganda. Their tiles comprised mainly of sand and plastic waste are manufactured in an industrialized process involving drying, extrusion, and pressing. The exergy consumed at each stage including transportation is presented. The extruder consumes the majority of the exergy, but wrapping insulation around the barrel could save over 3 MJ, and a heat engine could provide over 7.5 MJ of usable exergy. The total exergy consumed to produce one batch of seventy-five tiles is over 122 MJ, the potentially recoverable exergy is over 5 MJ (4.3% of consumed exergy), and the realistic recoverable exergy is nearly 10.7 MJ (8.7% of consumed exergy). The realistic can be greater than the potential by adding a heat engine to the sand drying process to generate usable exergy rather than merely recover consumed exergy. Resintile’s plastic roof tiles save a net 86.3 kg of CO2 from entering the atmosphere per batch of tiles and adoption of the suggested improvements to the manufacturing process would save an additional 3.8 kg of CO2 per batch.
Assessment of a CFD-Based Machine Learning Approach on Turbulent Flow Approximation
Authors: Ziaei Dorsa , Hekmati Athar Seyyed Pooya , Goudarzi Navid 
Published: December 2019

Abstract
Computational fluid dynamics (CFD) simulation is usually a computationally expensive, memory demanding, and time consuming iterative process. These drawbacks limit the use of CFD, especially when either spatiotemporal scales or geometry complexity increases. This paper presents the preliminary results from the assessment of an approximation model for predicting non-uniform steady turbulent flows in a 3D domain, utilizing deep learning (DL) algorithms. In particular, the artificial neural network (ANN) approach uses most important variables data from currently CFD simulation results to link multi-variable input spaces (e.g. input speed and direction, geometry configuration) with multi-variable output space (e.g. velocity magnitude, pressure gradient) to obtain an efficient and accurate approximation of the entire velocity field for given input flow field characteristics. The results demonstrated higher computational speed with a similar accuracy using DL algorithms versus CFD simulation. This integrated approach can provide immediate feedback for real-time design iterations for the entire computational domain at the early stages of design. Hence, designers and engineers can easily generate immense amounts of design alternatives without facing the time-consuming task of evaluation and selection.
Supercritical Water Gasification of Ethanol for Fuel Gas Production
Authors: Pinkard Brian R. , Rasmussen Elizabeth G. , Kramlich John C. , Reinhall Per G. , Novosselov Igor V. 
Published: December 2019

Abstract
Supercritical water gasification of dilute ethanol at the industrial scale promises a sustainable route to bio-syngas production for use in combined cycle power plants. Cost-effective bio-syngas production would reduce reliance on fossil fuels for electricity generation and reduce greenhouse gas emissions by utilizing waste biomass resources. Continuous supercritical water gasification offers high reactant conversion at short residence times without an added catalyst. The decomposition of ethanol in supercritical water is studied in a continuous reactor at 560 °C, 25 MPa, residence times between 3 and 8 s, and a constant initial ethanol concentration of 8.1 wt%. High-resolution, in-situ Raman spectroscopy facilitates identification of reaction products. Significant yields of H2, CO, and CH4 indicate the dominance of a dehydrogenation reaction pathway at studied conditions, while minor yields of ethane indicate a secondary dehydration reaction pathway. Ethylene yields are virtually nonexistent, indicating rapid hydrogenation of ethylene to ethane at these conditions. Ethanol dehydrogenation to H2, CO, and CH4 results in an overall fuel value upgrade of 84.5 kJ/mol-EtOH. Dehydration of ethanol to ethane results in an overall fuel degradation of −3.8 kJ/mol-EtOH.
Numerical Simulation of a Composite Metal Foam-PCM Air Heat Exchanger Using Rod PTC Heating Elements
Authors: Talebizadeh Sardari Pouyan , Giddings Donald , Walker Gavin S. , Gillott Mark , Grant David 
Published: December 2019

Abstract
The aim of this paper is to study the charging/discharging process in a Latent heat exchanger for the purpose of space heating by using a composite metal foam/PCM. The composite PCM-air system is modelled in a 3-D CFD approach for the purpose of 8h charging during the night and 16h discharging during the daytime using the non-equilibrium thermal model to simulate the presence of a porous medium in the domain. For the charging process, rod Positive Temperature Coefficient (PTC) heating elements with constant temperature are selected to heat the PCM based on the maximum operating temperature of the PCM. For the discharging process, a blower is assumed to pass the air from the middle of the PCM container and so the air can gain heat and its temperature rises which is used then for space heating. RT70HC is also selected as the PCM material due to the high capacity of latent heat and suitable melting point for domestic usage. The system is studied according to the average liquid fraction and temperature of the PCM during both charging and discharging as well as the outlet temperature of the air during discharging. The results show that by using two rod heating elements with the diameter of 1cm, length of 25cm and temperature of 95°C, the melting process is performed in less than 8h. Furthermore, a uniform output temperature of almost 29.5°C is also achieved in the next 16h during the discharging process with the air mass flow rate of 0.04 kg/s.
Powder-Binder Jetting Large-Scale, Metal Direct-Drive Generators: Selecting the Powder, Binder, and Process Parameters
Authors: Hayes Austin C. , Whiting Gregory L. 
Published: December 2019

Abstract
Additive manufacturing enables the production of complex geometries extremely difficult to create with conventional subtractive methods. While good at producing complex parts, its limitations can be seen through its penetration into everyday manufacturing markets. Throughput limitations, poor surface roughness, limited material selection, and repeatability concerns hinder additive manufacturing from revolutionizing all but the low-volume, high-value markets. This work characterizes combining powder-binder jetting with traditional casting techniques to create large, complex metal parts. Specifically, we extend this technology to wind turbine generators and provide initial feasibility of producing complex direct-drive generator rotor and stator designs. In this process, thermal inkjet printer heads selectively deposit binder on hydroperm casting powder. This powder is selectively solidified and baked to remove moisture before being cast through traditional methods. This work identifies a scalable manufacturing process to print large-scale wind turbine direct drive generators. As direct-drive generators are substantially larger than their synchronous counterparts, a printing process must be able to be scaled for a 2–5 MW 2–6m machine. For this study, research on the powder, binder, and printing parameters is conducted and evaluated for scalability.
Supercritical CO2 Brayton Power Cycle for CSP With Packed Bed TES Integration and Cost Benchmark Evaluation
Authors: Trevisan Silvia , Guédez Rafael , Laumert Björn 
Published: December 2019

Abstract
The present work introduces an indirect supercritical CO2–air driven concentrated solar plant with a packed bed thermal energy storage. The proposed plant design enables a supercritical CO2 turbine inlet temperature of 800°C, overcoming the temperature limits imposed by the use of solar molten salts as primary heat transfer fluid. Furthermore, the packed bed thermal energy storage permits the decoupling between thermal power collection from the sun and electricity generation. Besides, the thermal energy storage unit grants operational flexibility and enlarges the plant capacity factor, making it as available as a conventional coal facility. A transient thermodynamic model of the integrated concentrating solar plant, including receiver, thermal energy storage, intermediate heat exchangers and supercritical CO2 power cycle has been developed. This same model has been used to evaluate the thermodynamic performance of the proposed plant design over a complete year. A similar model has been implemented to simulate a supercritical CO2 plant driven by a more traditional solar molten salt loop. A comparison of the thermodynamic performance of the two plant designs has been performed. A complete economic model has been developed in order to evaluate the economic viability of the proposed plant. Furthermore, a multi-objective optimization have been executed in order to assess the influence of the thermal energy storage size, supercritical CO2 turbine inlet temperature and plant solar multiple on the key performance indicators. Results show that the proposed indirect supercritical CO2–air driven with a packed bed thermal energy storage concentrated solar plant leads to improved thermo-economic performance with respect to the molten salts driven design. Enhancements in the power cycle efficiency and in the overall electricity production can be achieved, with a consequent reduction in the levelized cost of electricity. Particularly, for a design net electrical power production of 10MWe a minimum levelized cost of electricity has been calculated at 89.4 $/MWh for a thermal energy storage capacity of 13.9 hours at full load and a plant solar multiple of 2.47 corresponding to a capital investment of about 73.4 M$.