Distributed decision-making in the shadow of hierarchy:How hierarchical similarity biases idea evaluation

Research Summary: Companies are increasingly opening up decision-making, involving employees on all levels in distributed—and purportedly “hierarchy-free”—decision processes. We examine how hierarchy reaches into such “democratized” systems, arguing that it is a source of homophily that biases idea evaluation decisions. Using a data set from internal crowdfunding at one of the world's largest industrial manufacturers, we show that idea evaluators overvalue hierarchically similar others' ideas. Competition in the form of lateral closeness dampens this bias, whereas uncertainty in the form of novelty amplifies this bias. We contribute to the literatures on decision biases in centralized versus distributed innovation and on structural similarity as a driver of employee behaviors. Managerial Summary: Many companies are starting to involve employees on all levels in strategic decisions, so as to curb hierarchical rigidities and integrate multiple perspectives. However, such distributed decision-making opens the door to new biases and, ultimately, suboptimal strategic decisions. In the context of internal crowdfunding at a large industrial manufacturer, we show that employees evaluate hierarchically similar others' ideas overly favorably. Thus, hierarchy is not just a source of rivalry, but also of identification, leading to favoritism among hierarchical peers. Further, employees are particularly likely to assess ideas based on hierarchical similarity rather than content if the ideas are novel and therefore hard to evaluate. We provide suggestions for the design of distributed decision-making systems.</p

Study of material homogeneity in the long fiber thermoset injection molding process by image texture analysis

To quantify the homogeneity of fiber dispersion in short fiber-reinforced polymer composites, a method for image texture analysis of 3-dimensional X-ray micro computed tomography (µCT) images is presented in this work. The adaption of the method to the specific requirements of the composite material is accomplished using a statistical region merging approach. Subsequently, the method is applied for evaluating the homogeneity of specimens from an intermediate step of the long fiber thermoset injection molding process as well as molded parts. This new injection molding process enables the manufacturing of parts with a flexible combination of short and long glass fibers. By using a newly developed screw element based on the Maddock mixing element design, the material homogeneity of parts molded in the long fiber injection molding process is improved

Magnetoresistance of UPt3

We have performed measurements of the temperature dependence of the magnetoresistance up to 9 T in bulk single crystals of UPt3 with the magnetic field along the b axis, the easy magnetization axis. We have confirmed previous results for transverse magnetoresistance with the current along the c axis, and report measurements of the longitudinal magnetoresistance with the current along the b axis. The presence of a linear term in both cases indicates broken orientational symmetry associated with magnetic order. With the current along the c axis the linear term appears near 5 K, increasing rapidly with decreasing temperature. For current along the b axis the linear contribution is negative.Comment: 6 pages, 3 figures, submitted to Quantum Fluids and Solids Conference (QFS 2006

Novel imaging closed loop control strategy for heliostats

Central Receiver Systems use up to thousands of heliostats to concentrate solar radiation. The precise control of heliostat aiming points is crucial not only for efficiency but also for reliable plant operation. Besides the calibration of open loop control systems, closed loop tracking strategies are developed to address a precise and efficient aiming strategy. The need for cost reductions in the heliostat field intensifies the motivation for economic closed loop control systems. This work introduces an approach for a closed loop heliostat tracking strategy using image analysis and signal modulation. The approach aims at the extraction of heliostat focal spot position within the receiver domain by means of a centralized remote vision system decoupled from the rough conditions close to the focal area. Taking an image sequence of the receiver while modulating a signal on different heliostats, their aiming points are retrieved. The work describes the methodology and shows first results from simulations and practical tests performed in small scale, motivating further investigation and deployment

Towards complete tree crown delineation by instance segmentation with Mask R–CNN and DETR using UAV-based multispectral imagery and lidar data

Precise single tree delineation allows for a more reliable determination of essential parameters such as tree species, height and vitality. Methods of instance segmentation are powerful neural networks for detecting and segmenting single objects and have the potential to push the accuracy of tree segmentation methods to a new level. In this study, two instance segmentation methods, Mask R–CNN and DETR, were applied to precisely delineate single tree crowns using multispectral images and images generated from UAV lidar data. The study area was in Bavaria, 35 km north of Munich (Germany), comprising a mixed forest stand of around 7 ha characterised mainly by Norway spruce (Picea abies) and large groups of European beeches (Fagus sylvatica) with 181–236 trees per ha. The data set, consisting of multispectral images and lidar data, was acquired using a Micasense RedEdge-MX dual camera system and a Riegl miniVUX-1UAV lidar scanner, both mounted on a hexacopter (DJI Matrice 600 Pro). At an altitude of approximately 85 m, two flight missions were conducted at an airspeed of 5 m/s, leading to a ground resolution of 5 cm and a lidar point density of 560 points/m2. In total, 1408 trees were marked by visual interpretation of the remote sensing data for training and validating the classifiers. Additionally, 125 trees were surveyed by tacheometric means used to test the optimized neural networks. The evaluations showed that segmentation using only multispectral imagery performed slightly better than with images generated from lidar data. In terms of F1 score, Mask R–CNN with color infrared (CIR) images achieved 92% in coniferous, 85% in deciduous and 83% in mixed stands. Compared to the images generated by lidar data, these scores are the same for coniferous and slightly worse for deciduous and mixed plots, by 4% and 2%, respectively. DETR with CIR images achieved 90% in coniferous, 81% in deciduous and 84% in mixed stands. These scores were 2%, 1%, and 2% worse, respectively, compared to the lidar data images in the same test areas. Interestingly, four conventional segmentation methods performed significantly worse than CIR-based and lidar-based instance segmentations. Additionally, the results revealed that tree crowns were more accurately segmented by instance segmentation. All in all, the results highlight the practical potential of the two deep learning-based tree segmentation methods, especially in comparison to baseline methods

Linear Fresnel Collector Mirrors - Measured Systematic Surface Errors and their Impact on the Focal Line

Objective of this article is to show and discuss the shape accuracy of solar reflector panels for linear Fresnel collectors. Systematic shape deviations due to torsion or orientation errors are responsible for severe optical losses and underperformance. This is why this article investigates systematic surface deviations beyond the standard quality parameters like SDx and FDy. We discuss typical characteristics of linear Fresnel collector reflector panels. Our measurement results show local surface slope deviations measured by deflectometry. In the second part of this study, the effect of systematic surface slope deviations is analyzed by use of a parametric model. We apply the model to detect systematic production errors, investigate optical losses and the impact on the focal line with ray tracing

Novel sky discretization method for optical annual assessment of solar tower plants

Optical assessment of Central Receiver Solar Tower systems should be based on annual simulations due to the high variability of solar radiation throughout the year. The most basic approach is using a discretization of the temporal domain which requires a large number of computationally costly optical simulations. This study proposes an alternative approach based on a discretization of the sky which reduces the required number of simulations and therefore the computational effort significantly. For the subsequent annual performance assessment data three different interpolation methods are presented, compared and their respective advantages and drawbacks are discussed. The methodology is demonstrated by means of three representative heliostat field setups: the PS10 field, the Gemasolar field and a small, generic field. In this context, the dependency of the interpolation accuracy with respect to the resolution of the sky grid is investigated

Techno-Economic Assessment of New Material Developments in Central Receiver Solar Power Plants

For the evaluation of functional material developments in the EU-project RAISELIFE, a tool chain of ray tracing, thermal FEM simulation and dynamic system simulation has been created. Multi-year simulations allow considering degradation of optical parameters. With this tool chain, the thermal energy output of a reference plant with one non-selective and one generic selective coating was simulated. The LCOE (Levelized Cost of Electricity) was calculated based on these results. The LCOE of the selective coating is 2.6 % lower, if the same costs are assumed. Furthermore, the ideal recoating interval for the reference system was identified. Finally, it was demonstrated that dynamic system simulation shows benefits to evaluate in-service performance of functional materials as dynamic behavior of solar thermal power plants can change quite significantly, if another coating is used

Solar tower cavity receiver aperture optimization based on transient optical and thermo-hydraulic modeling

A transient simulation methodology for cavity receivers for Solar Tower Central Receiver Systems with molten salt as heat transfer fluid is described. Absorbed solar radiation is modeled with ray tracing and a sky discretization approach to reduce computational effort. Solar radiation re-distribution in the cavity as well as thermal radiation exchange are modeled based on view factors, which are also calculated with ray tracing. An analytical approach is used to represent convective heat transfer in the cavity. Heat transfer fluid flow is simulated with a discrete tube model, where the boundary conditions at the outer tube surface mainly depend on inputs from the previously mentioned modeling aspects. A specific focus is put on the integration of optical and thermo-hydraulic models. Furthermore, aiming point and control strategies are described, which are used during the transient performance assessment. Eventually, the developed simulation methodology is used for the o ptimization of the aperture opening size of a PS10-like reference scenario with cavity receiver and heliostat field. The objective function is based on the cumulative gain of one representative day. Results include optimized aperture opening size, transient receiver characteristics and benefits of the implemented aiming point strategy compared to a single aiming point approach. Future work will include annual simulations, cost assessment and optimization of a larger range of receiver parameters

Efficient modeling of variable solar flux distribution on solar tower receivers by interpolation of few discrete representations

In order to assess the solar radiation on the complex geometry of Solar Tower receivers, usually detailed maps of the flux distribution are generated using optical simulations based on ray tracing techniques. Transient modeling including a large set of such simulations implies very high computational effort. A new methodology is presented which allows for transient assessment of the flux distribution based on a comparatively small set of optical simulations and subsequent interpolations. For this purpose, two different discretization grids are used: a set of uniformly distributed solar vector nodes on the sky hemisphere and a set of different heliostat field fractions being on focus. For the interpolation in the sky discretization, three different techniques are introduced and compared in terms of accuracy. Partly defocused heliostat fields as well as complex aiming strategies can be readily taken into account by the presented approach. The methodology is validated by means of two exemplary test setups (PS10 and Gemasolar). The accuracy of the different interpolation techniques depending on the refinement of the discretization grids is assessed with appropriate error measures. Depending on the temporal resolution of the transient application, the computational effort can be reduced by several orders of magnitude compared to a direct simulation of the flux distribution for every time step. In addition to the quantitative validation, the use of the developed methodology in conjunction with a thermo-hydraulic simulation is demonstrated by means of the PS10 setup