Indoor mould growth prediction using coupled computational fluid dynamics and mould growth model

This study investigates, using in-situ and numerical simulation experiments, airflow and hygrothermal distribution in a mechanically ventilated academic research facility with known cases of microbial proliferations. Microclimate parameters were obtained from in-situ experiments and used as boundary conditions and validation of the numerical experiments with a commercial computational fluid dynamics (CFD) analysis tool using the standard k–ε model. Good agreements were obtained with less than 10% deviations between the measured and simulated results. Subsequent upon successful validation, the model was used to investigate hygrothermal and airflow profile within the shelves holding stored components in the facility. The predicted in-shelf hygrothermal profile was superimposed on mould growth limiting curve earlier documented in the literature. Results revealed the growth of xerophilic species in most parts of the shelves. The mould growth prediction was found in correlation with the microbial investigation in the case-studied room reported by the authors elsewhere. Satisfactory prediction of mould growth in the room successfully proved that the CFD simulation can be used to investigate the conditions that lead to microbial growth in the indoor environment

A Fast Potential and Self-Gravity Solver for Non-Axisymmetric Disks

Disk self-gravity could play an important role in the dynamic evolution of interaction between disks and embedded protoplanets. We have developed a fast and accurate solver to calculate the disk potential and disk self-gravity forces for disk systems on a uniform polar grid. Our method follows closely the method given by Chan et al. (2006), in which an FFT in the azimuthal direction is performed and a direct integral approach in the frequency domain in the radial direction is implemented on a uniform polar grid. This method can be very effective for disks with vertical structures that depend only on the disk radius, achieving the same computational efficiency as for zero-thickness disks. We describe how to parallelize the solver efficiently on distributed parallel computers. We propose a mode-cutoff procedure to reduce the parallel communication cost and achieve nearly linear scalability for a large number of processors. For comparison, we have also developed a particle-based fast tree-code to calculate the self-gravity of the disk system with vertical structure. The numerical results show that our direct integral method is at least two order of magnitudes faster than our optimized tree-code approach.Comment: 8 figures, accepted to ApJ

Realization of a 10 kW MES power to methane plant based on unified AC/DC converter

This paper presents a galvanic isolated multi output AC/DC topology that is suitable for Microbial electrosynthesis (MES) based Power to Methane energy storage systems. The presented scheme utilizes a three phase back to back converters, a single-input and multiple-output three phase transformer, single diode rectifiers and buck converters that employ a proper interconnection between MES cells and the mains. The proposed topology merges all the required single phase AC/DC converters as a unified converter which reduces the overall system size and provides system integrity and overall controllability. The proposed control scheme allows to achieve the following desired goals:1) Simultaneous control of all cells; 2) Absorbing power from the grid and covert to methane when the electricity price goes down; 3) the power factor and the quality of grid current is under control; 4) Supplying MES cells at the optimal operating point. For verification of system performance, Real time simulation results that are obtained from a 10-kW MES energy storage are presented.Postprint (author's final draft

Contributions to the Sixth Drag Prediction Workshop Using Structured, Overset Grid Methods

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143028/1/1.C034486.pd

Path-tracing Monte Carlo Library for 3D Radiative Transfer in Highly Resolved Cloudy Atmospheres

Interactions between clouds and radiation are at the root of many difficulties in numerically predicting future weather and climate and in retrieving the state of the atmosphere from remote sensing observations. The large range of issues related to these interactions, and in particular to three-dimensional interactions, motivated the development of accurate radiative tools able to compute all types of radiative metrics, from monochromatic, local and directional observables, to integrated energetic quantities. In the continuity of this community effort, we propose here an open-source library for general use in Monte Carlo algorithms. This library is devoted to the acceleration of path-tracing in complex data, typically high-resolution large-domain grounds and clouds. The main algorithmic advances embedded in the library are those related to the construction and traversal of hierarchical grids accelerating the tracing of paths through heterogeneous fields in null-collision (maximum cross-section) algorithms. We show that with these hierarchical grids, the computing time is only weakly sensitivive to the refinement of the volumetric data. The library is tested with a rendering algorithm that produces synthetic images of cloud radiances. Two other examples are given as illustrations, that are respectively used to analyse the transmission of solar radiation under a cloud together with its sensitivity to an optical parameter, and to assess a parametrization of 3D radiative effects of clouds.Comment: Submitted to JAMES, revised and submitted again (this is v2

Scalable Analysis, Verification and Design of IC Power Delivery

Due to recent aggressive process scaling into the nanometer regime, power delivery network design faces many challenges that set more stringent and specific requirements to the EDA tools. For example, from the perspective of analysis, simulation efficiency for large grids must be improved and the entire network with off-chip models and nonlinear devices should be able to be analyzed. Gated power delivery networks have multiple on/off operating conditions that need to be fully verified against the design requirements. Good power delivery network designs not only have to save the wiring resources for signal routing, but also need to have the optimal parameters assigned to various system components such as decaps, voltage regulators and converters. This dissertation presents new methodologies to address these challenging problems. At first, a novel parallel partitioning-based approach which provides a flexible network partitioning scheme using locality is proposed for power grid static analysis. In addition, a fast CPU-GPU combined analysis engine that adopts a boundary-relaxation method to encompass several simulation strategies is developed to simulate power delivery networks with off-chip models and active circuits. These two proposed analysis approaches can achieve scalable simulation runtime. Then, for gated power delivery networks, the challenge brought by the large verification space is addressed by developing a strategy that efficiently identifies a number of candidates for the worst-case operating condition. The computation complexity is reduced from O(2^N) to O(N). At last, motivated by a proposed two-level hierarchical optimization, this dissertation presents a novel locality-driven partitioning scheme to facilitate divide-and-conquer-based scalable wire sizing for large power delivery networks. Simultaneous sizing of multiple partitions is allowed which leads to substantial runtime improvement. Moreover, the electric interactions between active regulators/converters and passive networks and their influences on key system design specifications are analyzed comprehensively. With the derived design insights, the system-level co-design of a complete power delivery network is facilitated by an automatic optimization flow. Results show significant performance enhancement brought by the co-design