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A permanent magnet synchronous reluctance machine (PMSynRM) is studied in this paper. It has a stack of surface-mounted permanent magnet (SPM) rotor and a stack of synchronous reluctance (SynR) rotor, which are axially combined on the shaft. Unlike the traditional PM-assisted SynR machine (PMASynRM), the magnets are not located in the flux barriers of the SynR rotor, therefore, the magnets and flux barriers have no more geometric confliction between them. The two rotor stacks can be circumferentially shifted to any relative angle. Clearly, the shifting angle and the axial length ratio between the two rotor stacks, together with the phase angle of the armature current vector, influence the motor performance, and their optimal design is detailed in this paper. Analysis of the prototypes shows that the studied PMSynRM evidently exhibits higher torque density than the conventional PMASynRM.

Asymmetrical rotor topologies were previously proposed for synchronous reluctance motors (SynRM) to reduce the torque ripple. However, potential negative effect of these topologies on mechanical vibration, which is often serious in SynRM, was hardly studied and such an effect is investigated here. An analytical model is established, through which the spatial orders of the radial electromagnetic force with various rotor topologies are derived, and the relationship of the peak frequencies and the corresponding spatial orders in the radial electromagnetic force is revealed. It is shown that some asymmetric rotor topologies will reduce the order of the lowest spatial harmonic for the radial electromagnetic force, and consequently increase the vibration. Finite element analysis and experiments demonstrate the same results. Finally, a specific rotor topology with asymmetry about both d‐axis and q‐axis is recommended, which can reduce the torque ripple, but would not deteriorate the radial electromagnetic force and vibration.

One of the main challenges in motor design is the winding layout, including winding distributions and magnetomotive force (MMF) harmonic analysis. Considering some shortcomings in the existing theories for winding distributions and difficulties in dealing with unconventional fractional-slot windings, a unified theory of symmetric winding distributions is proposed. First, this study gives the sufficient and necessary conditions for a m-phase symmetric winding and the novel winding distribution formula. Subsequently, a general method for MMF harmonic analysis including the amplitude of MMF harmonics and harmonic orders are proposed. Finally, the analysis results show that this unified theory is an efficient and compact method to deal with the winding layout to analyse all kinds of winding MMF harmonics.

This paper studies spurious regressions involving processes moderately deviated from a unit root (PMDURs), and establishes the limiting distributions for the least squares estimator, the associated t -statistic, the coefficient of determination R 2 and the Durbin–Watson statistic. We find that these limiting distributions critically depend on nuisance parameters that characterize the local deviations from unity, making inference for spurious regressions practically impossible using the conventional t -statistic. As a cure, we propose robust inference based on the balanced regression model, where the lagged regressor and the lagged dependent variable are augmented to the original regression. The induced t -statistic via such an augmentation is shown to be asymptotically standard normal and is therefore free of nuisance parameters, which turns out to be a robust and simple-to-implement tool for spurious regressions inference. Moreover, the limiting properties of other statistics are investigated. The balanced regression based inference is further shown to continue to work for cointegration models with PMDURs, which is therefore robust to whether the PMDURs are spuriously related or cointegrated. Finally, the finite sample properties of the robust method are demonstrated through both Monte Carlo and real data examples.

In recent years statistical inference for nonlinear cointegration has attracted attention from both academics and practitioners. This paper proposes a new type of cointegration in the sense that two univariate time series yt and xt are cointegrated via two (unknown) smooth nonlinear transformations, further generalizing the notion of cointegration initially revealed by Box and Tiao (1977), and more systematically studied by Engle and Granger (1987). More precisely, it holds that G(yt,β0)=g(xt)+ut, where G(⋅,β0) is strictly increasing and known up to an unknown parameter β0, g(⋅) is unknown and smooth, xt is I(1), and ut is the stationary disturbance. This setting nests the nonlinear cointegration model of Wang and Phillips (2009b) as a special case with G(y,β0)=y. It extends the model of Linton et al. (2008) to the cases with a unit-root nonstationary regressor. Sieve approximations to the smooth nonparametric function g are applied, leading to an extremum estimator for β and a plugging-in estimator for g(⋅). Asymptotic properties of the estimators are established, revealing that both the convergence rates and the limiting distributions depend intimately on the properties of the two nonlinear transformation functions. Simulation studies demonstrate that the estimators perform well even with small samples. A real data example on the environmental Kuznets curve portraying the nonlinear impact of per-capita GDP on air-pollution illustrates the practical relevance of the proposed double-nonlinear cointegration.

Recalcitrance of lignocellulosic feedstocks to depolymerization is a significant barrier for bioenergy production approaches that require conversion of monomeric carbohydrates to renewable energy sources. This study assesses how low‐cost modifications in the supply chain can be transformed into targeted pretreatments in the context of the entire bioenergy supply chain. This research aims to overcome the physiochemical barriers in corn stover that necessitate increased severity in downstream conversion in terms of chemical loading, temperature, and residence time. Corn stover samples were inoculated with a selective (Ceriporiopsis subvermispora) and nonselective (Phanerochaete chrysosporium) lignin‐degrading filamentous fungal strains, then stored aerobically to determine the working envelope for fungal pretreatment to achieve lignin degradation. Dry matter loss and gross chemical makeup of corn stover varied by the length of treatment (2 and 4 weeks) and by the moisture content of the treated corn stover samples (40% and 60%, wet basis). Dry matter loss in P. chrysosporium inoculated biomass was elevated compared to C. subvermispora inoculated biomass; however, treatment also induced additional chemical composition changes suggestive of depolymerization. These results highlight that fungal treatment approaches must balance the loss of convertible material with the potential for reduction in recalcitrance. Techno‐economic assessment (TEA) of fungal pretreatment in a short‐term queuing system indicated the viability of this approach compared to conventional queuing operations. Total queuing system cost was estimated at $1.65/ton of biomass stored. After applying the credit of $1.48/ton from energy savings in the conversion phase using fungal pretreated biomass, the total system cost was $0.80 lower than traditional biomass queuing approach. While the TEA results suggested that treating biomass with C. subvermispora is the most economically viable storage method in the designed fungal‐assisted queuing system, future research should focus on additional fungal depolymerization such as those observed in the P. chrysosporium inoculated biomass.

The environmental and economic impacts of implementing a circular economy in plastic waste supply chains are not well understood. The proposed systems analysis framework assesses environmental, social, and economic impacts of plastic waste supply chains in a circular economy. The first objective of this article is to identify data sets, models, and knowledge gaps associated with waste plastic supply chain processes, mainly in the U.S. Our literature review indicated that the best data sets exist for virgin plastic resin production, mechanical recycling, landfilling, and incineration, with the materials recovery facility being intermediate, and with chemical recycling the lowest. The second objective of this perspective is to develop an illustrative application of the framework by conducting a preliminary systems analysis of PET bottles with closed-loop recycling. The preliminary systems analysis of polyethylene terephthalate (PET) bottles utilized a linear programming optimization method. Our optimization model indicated that both chemical and mechanical recycling processes are needed to achieve a true circular economy of PET bottles with the least greenhouse gas emissions, specifically reductions of 24% when compared with the linear economy. Good quality and standardized life cycle assessment and techno-economic analysis studies are needed to better understand the environmental, economic, and social impacts of advanced sorting and chemical recycling technologies.

This paper investigates an axially segmented PMASynRM with hybrid rotor, which consists of synchronous reluctance rotor and surface-mounted rotor. Through extracting the permanent magnet from the multi-layered flux barriers and forming a single SPM rotor, the axially segmented SynRM well addresses the manufacturing problem existing in the traditional PMASynRM. Meanwhile, by optimizing the critical parameters in the hybrid rotor, the axially segmented PMASynRM can have a higher power density while keep the power factor constant compared with the traditional PMASynRM. Finally, the electromagnetic performance of the optimized axially segmented PMASynRM is compared with traditional PMASynRM, and it is proved the axially segmented PMASynRM has higher power density and power factor.

The world is witnessing an unprecedented generation and accumulation of fiber-plastic wastes resulting in various challenges due to inconsistency, waste-stream heterogeneity, conveying issues, self-heating, and difficulty in pelletization. This study presents a novel pilot-scale system that integrates torrefaction and extrusion to convert mix fiber-plastic waste into fuel pellets. The produced pellets have low cost, high heating value, better uniformity, and low environmental impact. They can be used as solid fuels or as feedstock for pyrolysis and gasification. To evaluate the pellet cost and its environmental impact, we performed Techno-Economic Analysis (TEA) and Life Cycle Assessment (LCA). The TEA integrates research findings from the torrefaction-extrusion project with the techno-economic models and estimates the costs, energy consumption, and mass balances for pelletizing and torrefaction. The analysis indicates that the baseline cost of producing uniform pellets is about $55.28/dry tonne (2020$). LCA results indicate that the torrefied product has cradle-to-gate embodied greenhouse gas emissions that are net negative, although they are higher than a comparable forest-derived woodchip product. Fossil energy demand for the torrefied product is lower than the forest-derived chip, indicating the torrefied product has strong potential for use as an environmentally beneficial feedstock for future processing.

The commercial development of biofuels and bioproducts depends on whether renewable biomass feedstock is available while not directly competing with the production of food. Farmers are one of the most important stakeholders in the biofuel supply chain and confront a range of uncertainties while entering the bioenergy market. Their decision-making process is extremely complex and rarely purely rational. Modeling farmer behavior requires considering a wide range of individual-level factors, socio-temporal dynamics, institutional settings, and their interactions. These characteristics make agent-based modeling a suitable framework for evaluating such systems. We developed a model to simulate farmer bioenergy crop adoption behavior across a 50-county study region in Nebraska, Kansas, and Colorado. The analysis considers adoption decisions for two bioenergy feedstocks, crop residues and energy crops. We examine the influence of individual and farm characteristics, market structure, social networks, and media influence on farmer adoption decisions. Our results indicate that different factors can have varied impacts on the speed of adoption for the crop residues and energy crops. Identifying levers that have the most impact on grower adoption can inform the design of interventions both from policy and private sector standpoints with important implications for the future the bioenergy industry.

The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Defining the future location and supply logistics of conversion plants is imperative to ultimately transform the nation’s renewable biomass resources into cost-competitive, high-performance feedstock for production of biofuels and bioproducts. Since the US has put restrictions on production levels of conventional biofuels from edible resources, the nation needs to plan for the widespread accessibility and development of the cellulosic biofuel scenario. Conventional feedstock supply systems will be unable to handle cellulosic biomass nationwide, making it essential to expand the industry with an advanced feedstock supply system incorporating a distributed network of preprocessing depots and conversion plants, or biorefineries. Current studies are mostly limited to designing supply systems for specific regions of the country. We developed a national database with potential locations for depots and biorefineries to meet the nation’s target demand of cellulosic biofuel. Blended feedstock with switchgrass and corn stover (harvested by either a two- or three-pass method) are considered in a Mixed Integer Linear Programming model to deliver on-spec biomass that considers both, a desired quantity and quality at the biorefinery. The model solves for a network of varying size depots that supply to biorefineries of 725,000 dry tons/year. A total delivered feedstock cost that is less than $79.07/dry tons (2016$) is evaluated for years 2022, 2030, and 2040. In 2022, 124 depots and 59 biorefineries could be supplied with 42.8 million dt of corn stover and switchgrass. In 2030 and 2040, the total accessible biomass could increase to 215% and 393% respectively when compared to 2022. However, an $8/dry tons reduction in targeted delivery cost could reduce total accessible biomass by 67%. Kansas, Nebraska, South Dakota and Texas were identified as potential states with a strong biofuel economy given that they had six or more biorefineries located in all scenarios. In some scenarios, Colorado, Alabama, Georgia, Minnesota, Mississippi and South Carolina would greatly benefit from a depot network as these could only deliver to a biorefinery in a nearby state. To elaborate the impact of a nationwide consideration, the findings were compared with existing literature for different US regions. We also present results for biorefinery capacities that are double, triple and quadruple in size.

Because of the greater demand in using woody biomass for bioenergy and bio-based products, feedstock supply chain optimization becomes more important to decrease supply chain logistics costs. As a primary component in the biomass feedstock supply chain, the storage of harvested woody biomass can directly affect transportation cost, biomass quality, and combustion efficiency. An improved operations system structured with linear programming was developed for minimizing the total cost of woody biomass preprocessing, storage, and transportation. The improved operations system was applied in a simulated case study for a power plant in Michigan. In addition, a simulated second feedstock end user was added to the operations system to further test the model. The results showed that the improved operations system could lower supply chain logistics costs, improve feedstock quality, and simultaneously meet the feedstock end user's demand. The sensitivity analysis indicated that the additional profit from se...

This paper proposes a transformed linear cointegration model of the form Λ ( y t , β 0 ) = x t ⊤ θ 1 0 + z t ⊤ θ 2 0 + u t , where Λ is a monotonic function, x t is the nonstationary vector regressor, z t is the stationary regressor, u t is the regression error, and β 0 , θ 1 0 , θ 2 0 are unknown parameters. This model offers a flexible nonlinear cointegration via the monotonic transformation of the dependent variable, and includes the conventional linear cointegration model as a special case. Asymptotic properties of the proposed estimators are established. Simulations demonstrate that the estimators perform well in small samples. A real data example on the purchasing power parity illustrates the practical merits of our model.

Reconfigured forage harvesting equipment utilized for plantation biomass harvesting and processing is highly productive but is expensive and not yet widely used in short rotation woody crop (SRWC) production systems. Traditional timber harvesting equipment, on the other hand, has been widely used for decades and can be adapted for use in SRWC plantations. Productivity of these traditional systems is not well understood when utilized in such plantations. To that end, productivity and costs were evaluated for a traditional ground-based system (feller-buncher, skidder, loader, and grinder) in a 3.1-ha small-diameter hybrid poplar plantation in Escanaba, Michigan, USA. Operation cycle time predictive models were developed from a time and motion analysis. Operation productivity and costs were generated and then compared with published data for a reconfigured forage harvesting system. Compared values between the two systems included: machine hourly rate, in dollars per scheduled machine hour ($/SMH), th...

This paper considers the estimation of a semiparametric transformation model, Λ ( y t , β 0 ) = g ( x t ) + u t , where Λ ( ⋅ , β 0 ) is a strictly increasing function known up to an l -dimensional parameter β 0 , g is an unknown link function. Hermite polynomial expansion is used to approximate the link function g , which leads to an extreme estimator for β 0 and a plug-in estimator for g . Asymptotic properties of the estimators are established. Simulation results demonstrate that the estimators perform well in finite samples. An example on Canadian occupation prestige is provided to illustrate the practical value of the proposed model.

Synchronous reluctance machine, permanent magnet assisted synchronous reluctance machine, and interior permanent magnet synchronous machine share the same kind of rotor topology. Comprehensive investigations on the correlation between the amount and function of the permanent magnets buried in the rotor have been carried out to reveal the intricate relationship of these machine types. Both circumferential and radial flux bridges are commonly employed to provide dependable rotor integrity in these machines. However, the flux bridge width has a tremendous bearing on both electromagnetic performance and mechanical ruggedness, especially for synchronous reluctance machine. In this paper, the active saturation method is hence applied in synchronous reluctance machine to strike the right balance between manufacturability and electromagnetic performance. A SkW@3000rpm synchronous reluctance machine with flux bridge width of 1mm has been optimized to realise the active saturation method. Moreover, the influence of permanent magnet location patterns on the active saturation method has been investigated in detail.

An air-drying process was designed to avoid material decomposition and eliminate the high cost involved in other drying and storage methods. This process, which involved no chipping of biomass at the harvest site, was tested at two study sites in Escanaba, Upper Peninsula, Michigan, from June to November 2011. The primary objective of this study was to evaluate the effect of air-drying on biomass moisture content (MC) and higher heating value (HHV) over field storage. In addition the impacts of different positions within a pile, biomass pile sizes, and weather conditions on biomass moisture change were also tested. Results showed that biomass MCs were significantly reduced during the 5-month field storage period. In addition, the biomass MCs at different positions within a biomass pile were found to be statistically uniform. Results further suggested that making a biomass pile smaller is an appropriate way to store woody biomass when it is scheduled for short-term use, while larger piles should b...

High rates of inorganic fertilizers are used in conventional intensive production systems such as Abies fraseri (fraser fir) cropping systems for Christmas trees. Groundcovers can be used as green mulches, help reduce the use of farm chemicals, and provide several environmental benefits. We investigated the performance of a low-input cropping system by combining two legume cover crops [Dutch white clover (Trifolium repens) and alfalfa (Medicago sativa)] in combination with low rates of inorganic fertilizers as a step toward a more sustainable production system. The randomized block design comprised one cover crop and one of three applications of reduced rate inorganic fertilizer (75%, 50%, and 25% of the recommended rate). A conventional system using herbicides for weed control and the 100% rate of inorganic fertilizer was used as a control. Parameters measured included tree morphology, foliar nitrogen concentration, soil mineral nitrogen, and nitrate-N leaching below the root zone. A significant positive growth response (height and diameter) was obtained in all alfalfa-based cropping systems. This was accompanied by foliar nutrient concentrations similar to conventional plots and a reduction in nitrate-N leaching. However, in white clover-based cropping systems, the growth response was reduced (both height and diameter), suggesting competition for soil resources. In addition, the total nitrate-N leaching was higher in this system, suggesting an imbalance between mineral nitrogen availability and use in white clover-based cropping systems. We conclude that if the potential competition between cover crops and trees can be properly managed, legume cover crops can be effectively used to make intensive production tree-based systems more sustainable. Further studies related to mineralization and macronutrient flows are needed before any definite recommendation can be made about the use of these systems in large-scale production systems.

Due to the greater demand in bioenergy and bio-based products, feedstock supply chain optimization is critical to decrease the logistics costs. As a primary phase in the biomass feedstock supply logistics, the storage of harvested biomass can directly affect transportation cost, biomass quality and its combustion efficiency. A model structured with linear programming was developed to determine an optimized biomass pre-processing, storage, and transportation strategy. The optimization model was applied in a simulated case study for an energy plant in Michigan. The results indicated that lower supply chain logistics costs and higher feedstock quality could be achieved by applying an optimized supply chain strategy while simultaneously meeting the feedstock user’s demand. The sensitivity analysis indicated that transportation distance had no impact on the supply chain logistics strategy. The additional profit brought by higher quality biomass can offset the increased transportation cost for up to 151 miles. Through biomass MC increases, logging residue pile is always the preferred storage method. The impact of biomass moisture content (MC) is concluded to be more significant when it is higher. Through the increase of biomass MC, more biomass is required to satisfy the same energy demand. In average, every 1% increase in biomass MC can result in $760.68 increase in total cost and 52.1 more green tons biomass to satisfy the four-month energy demands.