Christian Veje

Predictability and granular materials

Abstract Granular materials present a number of challenges to predictability. The classical description of a dense granular material is based on Coulomb friction. For a static array of grains, the Coulomb friction forces are typically underdetermined. If we are to make useful statements about such arrays, we must develop new approaches, including the development of statistical descriptions. Granular materials also show large fluctuations in the local forces. These fluctuations are quite sensitive to small perturbations in the packing geometry of the grains. In the past, they have typically been ignored. However, recent experiments and models are beginning to shed new light on their characteristics. This article briefly reviews some of this new work, and in particular presents experimental results characterizing fluctuations and the role of friction in granular materials.

Sensitivity study of multi-layer active magnetic regenerators using first order magnetocaloric material La(Fe,Mn,Si)13Hy

We present simulation results of multi-layer active magnetic regenerators using the solid-state refrigerant La(Fe,Mn,Si)13Hy. This material presents a large, however quite sharp, isothermal entropy change that requires a careful choice of number of layers and working temperature for multi-layer regenerators. The impact of the number of layers and the sensitivity to the working temperature as well as the temperature span are quantified using a one dimensional numerical model. A study of the sensitivity of variation in Curie temperature through a uniform and normal distribution is also presented. The results show that the nominal cooling power is very sensitive to the Curie temperature variation in the multi-layer regenerators. A standard deviation of the Curie temperature variation for a normal distribution less than 0.6 K is suggested in order to achieve sufficient performance of a 15-layer regenerator with Curie temperature spacing of 2 K.

Challenge: Advancing Energy Informatics to Enable Assessable Improvements of Energy Performance in Buildings

Within the emerging discipline of Energy Informatics people are researching, developing and applying information and communication technologies, energy engineering and computer science to address energy challenges. In this paper we discuss the challenge of advancing energy informatics to enable assessable improvements of energy performance in buildings. This challenge follows a long-standing goal within the built environment to develop processes that enable predictable outcomes. Implementing this goal in the research framework of energy informatics creates a need for establishing a new underlying assumption, which states that the impact of energy informatics solutions should be assessable. This assumption applies to particular building contexts and when solutions act simultaneously. Research based on this assumption will enable new sound processes for the built environment facilitating informed decision for adding intelligent solutions to buildings compared to only favoring passive building improvements.

Demand response in commercial buildings with an Assessable impact on occupant comfort

Electricity grids are facing challenges due to peak consumption and renewable electricity generation. In this context, demand response offers a solution to many of the challenges, by enabling the integration of consumer side flexibility in grid management. Commercial buildings are good candidates for providing flexible demand due to their volume and the stability of their loads. However, existing technologies and strategies for demand response in commercial buildings fail to enable services with an assessable impact on load changes and occupant comfort. In this paper we propose the ADRALOC system for Automated Demand Response with an Assessable impact on Loads and Occupant Comfort. This enhances the quality of demand response services from a grid management perspective, as these become predictable and trustworthy. At the same time building managers and owners can participate without worrying about the comfort of occupants. We present results from a case study in a real office building where we illustrate the advantages of the system (i.e., load sheds of 3kW within comfort limits). Presenting a better system for demand response in commercial buildings is a step towards enabling a higher penetration of intelligent smart grid solutions in commercial buildings.

Analysis of the thermal behavior of a LiFePO4 battery cell

This paper presents theory, experiments and numerical modeling results for the electrothermal analysis of Lithium Iron Phosphate (LiFePO4) battery cells. Thermal management of batteries is important for several reasons including thermal runaway and maintaining battery operating time. A battery pack is comprised of battery cells which are stacked together without cooling surfaces except for the pack outer surface. The central cells in the pack are therefore exposed to the risk of overheating. A model for a single specific commercial LiFePO4 battery cell is presented together with preliminary experiments and results for determination of heating sources during charging and discharging. Based on the experimental results we extract model parameters for use in the model. The experiments lead to relations for the cell surface temperature and the lump temperature of the cell. A reasonable agreement between experiments and the model is found and suggestions for further work is indicated.

Fluctuations and Flow for Granular Shearing

We present results from both simulation and experiment on a 2D granular shear-cell. The experiments determine the position of disks and their orientations over time, as well as the force on individual disks. We use computerized particle tracking techniques to achieve the former and photoelasticity to achieve the latter. The simulations use MD force laws and efficient algorithms to simulate as closely as possible the experimental system. We measure the radial dependence of velocities and their distributions. In particular we find that the azimuthal velocity decays exponentially to some background level within a distance of about 7 disk diameters from the shearing wheel. Experimentally the distribution of azimuthal velocities is found to have a complex, roughly bimodal distribution close the the shearing wheel which is indicative of a complex combination of slip, no-slip, and rolling processes at the boundary, and a more exponential distribution away from the shearing surface. The distribution of stresses shows a falloff which is approximately exponential at large forces, although it is probably not possible to determine which among competing models for force distributions best fits these results. The model can capture most but not all of the features seen in the experiment. The mean velocity profile, the qualitative nature of force chains and the distribution of velocities far from the shearing surface are well captured in the simulations. The velocity distribution near the shearing surface and the force distributions differ considerably between theory and experiment.

Modelling of the Heating Process in a Thermal Screw

The procedure of separating efficiently dry-stuff (proteins), fat, and water is an important process in the handling of waste products from industrial and commercial meat manufactures. One of the sub-processes in a separation facility is a thermal screw where the raw material (after proper mincing) is heated in order to melt fat, coagulate protein, and free water. This process is very energy consuming and the efficiency of the product is highly dependent on accurate temperature control of the process. A key quality parameter is the time that the product is maintained at temperatures within a certain threshold. A detailed mathematical model for the heating process in the thermal screw is developed and analysed. The model is formulated as a set of partial differential equations including the latent heat for the melting process of the fat and the boiling of water, respectively. The product is modelled by three components; water, fat and dry-stuff (bones and proteins). The melting of the fat component is captured as a plateau in the product temperature. The model effectively captures the product outlet temperature and the energy consumed. Depending on raw material composition, soft or dry, the model outlines the heat injection and screw speeds necessary to obtain optimal output quality.

Science in the Sandbox: Fluctuations, Friction and Instabilities

The study of granular materials is a novel and rapidly growing field. These materials are interest for a number of reasons, both practical and theoretical. They exhibit a rich of novel dyanamical states, and they exhibit ‘phases’-solid, liquid, and gas-that resemble conventional thermodynamic phases. However, the presence of strong dissipation through friction and inelasticity places these systems well outside the usual class of systems that can be explained by equilibrium thermodynamics. Thus, there are important challenges to create new kinds of statistical physics and new analytical descriptions for the mean and fluctuating behavior of these materials. We explore recent work that focuses on several important issues. These include force propagation and fluctuations in static and driven systems. It is well known that forces propagate through granular structures along networks-force chains, whose structure is a function of history. It is much less clear how to describe this process, and even what kind of structures evolve in physical experiments. After a brief overview of the field, we consider models of force propagation and recent experiments to test these models. Among the latter are experiments that probe force profiles at the base of sandpiles, and experiments that determine the Green’s function response to point perturbations in granular systems. We also explore the nature of force fluctuations in slowly evolving systems, particulary sheared granular systems. These can be very strong-with rms fluctuations in the force that are as strong as the mean force. Finally, we pursue the analogy between conventional phases of matter, where we particularly focus on the transition between fluid and solid granular states in the presence of sustained horizontal shaking.

A flexible control strategy for integration of DG sources into the power grid

This paper deals with a multi-objective control strategy for integration of distributed generation (DG) sources to the power grid. The proposed control technique can provide simultaneous compensation for active and reactive power, and harmonic current components of loads through integration of DG sources to the grid, which is the main contribution of this work over the other proposed methods. A dynamic model of the proposed DG model is first formulated in the stationary reference frame and then transformed into the synchronous orthogonal reference frame. The transformed variables are used in control of voltage source converter (VSC) as the heart of an interfacing system between DG sources and utility grid. By setting appropriate reference currents in the control loop of DG, the maximum available power of DG source will be injected to the grid with fast dynamic response, thereby achieving sinusoidal grid currents in phase with load voltages, while the required power of the load is more than the maximum injected power of DG to the grid. The effectiveness of the proposed control strategy is validated with injection of maximum available power from the DG source to the grid, increased power factor of the utility grid and reduced total harmonic distortion (THD) of grid current through simulation results under dynamic and steady-state operating conditions.

Room-level occupant counts, airflow and CO2 data from an office building

The area of occupant sensing is lacking public datasets to baseline and foster data-driven research. This abstract describes a dataset covering room-level occupant counts, in-room ventilation airflow and CO2 data from an office building. This dataset can among others be used for developing and evaluating data-driven algorithms for occupant sensing and building analytics.