A study in computational fluid dynamics for the determination of convective heat and vapour transfer coefficients

Convective heat and moisture transfer coefficients are required to simulate the performance of building envelope systems, for example, in the simulation of the drying of wood or brick cladding wetted by driving rain. Such coefficients are dependent on the velocity and type of the air flow, the air and material temperature, the moisture content of the material and the relative humidity of the air. Convective heat transfer coefficient correlations are readily available for many geometries and air flow conditions, but primarily for mechanical engineering applications. It is not so for convective mass transfer coefficients. Building physicists must often put up with values from literature that are not entirely adequate or perform measurements for the conditions under study. The overall goal of this work was to study the feasibility and accuracy of using computational fluid dynamics (CFD) to calculate convective heat and vapour transfer coefficients. The objectives were: (1) to validate the CFD simulation results for boundary layer velocity and temperature profiles for laminar and turbulent forced convection, and for turbulent natural convection; (2) to simulate vapor transfer between air and a porous material; and (3) to compare the calculated convective heat and vapor transfer coefficients with literature experimental data. Several CFD simulations were performed to calculate the boundary layer velocity and temperature profiles in different configurations. The calculated convective heat transfer coefficients were compared with analytical, semi-empirical and/or experimental results from literature. A grid sensitivity analysis was performed to determine the grid independent solutions for certain cases. The overall conclusion was that CFD accurately predicted the boundary layer velocity and temperature profiles and the convective heat transfer coefficients for the cases studied. In order to simulate vapour transfer between air and porous materials, a model was developed using CFD coupled with an external vapour transport model. CFD was used to model heat and water vapour transport in the air, including both convective and radiative heat transfer, and heat transport within the material. Vapour transport in the material was calculated externally and coupled with the CFD solution at specific time steps. A transient case of air flow over a drying wood sample was simulated using the developed model. A sensitivity analysis was performed on relevant model parameters, such as the material properties of the wood and flow conditions of the air laye

Digital Timing Control in SRAMs for Yield Enhancement and Graceful Aging Degradation

Embedded SRAMs can occupy the majority of the chip area in SOCs. The increase in process variation and aging degradation due to technology scaling can severely compromise the integrity of SRAM memory cells, hence resulting in cell failures. Enough cell failures in a memory can lead to it being rejected during initial testing, and hence decrease the manufacturing yield. Or, as a result of long-term applied stress, lead to in-field system failures. Certain types of cell failures can be mitigated through improved timing control. Post-fabrication programmable timing can allow for after-the-fact calibration of timing signals on a per die basis. This allows for a SRAM's timing signals to be generated based on the characteristics specific to the individual chip, thus allowing for an increase in yield and reduction in in-field system failures. In this thesis, a delay line based SRAM timing block with digitally programmable timing signals has been implemented in a 180 nm CMOS technology. Various timing-related cell failure mechanisms including: 1). Operational Read Failures, 2). Cell Stability Failures, and 3). Power Envelope Failures are investigated. Additionally, the major contributing factors for process variation and device aging degradation are discussed in the context of SRAMs. Simulations show that programmable timing can be used to reduce cell failure rates by over 50%

Design and Analysis of an Adjacent Multi-bit Error Correcting Code for Nanoscale SRAMs

Increasing static random access memory (SRAM) bitcell density is a major driving force for semiconductor technology scaling. The industry standard 2x reduction in SRAM bitcell area per technology node has lead to a proliferation in memory intensive applications as greater memory system capacity can be realized per unit area. Coupled with this increasing capacity is an increasing SRAM system-level soft error rate (SER). Soft errors, caused by galactic radiation and radioactive chip packaging material corrupt a bitcell’s data-state and are a potential cause of catastrophic system failures. Further, reductions in device geometries, design rules, and sensitive node capacitances increase the probability of multiple adjacent bitcells being upset per particle strike to over 30% of the total SER below the 45 nm process node. Traditionally, these upsets have been addressed using a simple error correction code (ECC) combined with word interleaving. With continued scaling however, errors beyond this setup begin to emerge. Although more powerful ECCs exist, they come at an increased overhead in terms of area and latency. Additionally, interleaving adds complexity to the system and may not always be feasible for the given architecture. In this thesis, a new class of ECC targeted toward adjacent multi-bit upsets (MBU) is proposed and analyzed. These codes present a tradeoff between the currently popular single error correcting-double error detecting (SEC-DED) ECCs used in SRAMs (that are unable to correct MBUs), and the more robust multi-bit ECC schemes used for MBU reliability. The proposed codes are evaluated and compared against other ECCs using a custom test suite and multi-bit error channel model developed in Matlab as well as Verilog hardware description language (HDL) implementations synthesized using Synopsys Design Compiler and a commercial 65 nm bulk CMOS standard cell library. Simulation results show that for the same check-bit overhead as a conventional 64 data-bit SEC-DED code, the proposed scheme provides a corrected-SER approximately equal to the Bose-Chaudhuri- Hocquenghem (BCH) double error correcting (DEC) code, and a 4.38x improvement over the SEC-DED code in the same error channel. While, for 3 additional check-bits (still 3 less than the BCH DEC code), a triple adjacent error correcting version of the proposed code provides a 2.35x improvement in corrected-SER over the BCH DEC code for 90.9% less ECC circuit area and 17.4% less error correction delay. For further verification, a 0.4-1.0 V 75 kb single-cycle SRAM macro protected with a programmable, up-to-3-adjacent-bit-correcting version of the proposed ECC has been fab- ricated in a commercial 28 nm bulk CMOS process. The SRAM macro has undergone neu- tron irradiation testing at the TRIUMF Neutron Irradiation Facility in Vancouver, Canada. Measurements results show a 189x improvement in SER over an unprotected memory with no ECC enabled and a 5x improvement over a traditional single-error-correction (SEC) code at 0.5 V using 1-way interleaving for the same number of check-bits. This is compa- rable with the 4.38x improvement observed in simulation. Measurement results confirm an average active energy of 0.015 fJ/bit at 0.4 V, and average 80 mV reduction in VDDMIN across eight packaged chips by enabling the ECC. Both the SRAM macro and ECC circuit were designed for dynamic voltage and frequency scaling for both nominal and low voltage applications using a full-custom circuit design flow

Development of a stochastic virtual smart meter data set for a residential building stock - methodology and sample data

Existing electricity smart meter data sets lack sufficient details on building parameters to evaluate the impact that home characteristics can have on electricity consumption. An extensive, open-source virtual smart meter (VSM) data set with corresponding building characteristics is provided. The methodology used to develop the VSM data is presented in detail. The data set consists of a variety of homes representative of a subset of the Canadian single-family home building stock. The building characteristics cover a wide range of values that are based on probability distributions developed using a segmentation and characterization process. The resulting framework and VSM data set can be used by researchers to develop classification models, verify load disaggregation algorithms, and for a variety of other purposes

Water, Energy, and Carbon Footprints of Bioethanol from the U.S. and Brazil

Driven by biofuel policies, which aim to reduce greenhouse gas (GHG) emissions and increase domestic energy supply, global production and consumption of bioethanol have doubled between 2007 and 2016, with rapid growth in corn-based bioethanol in the U.S. and sugar cane-based bioethanol in Brazil. Advances in crop yields, energy use efficiency in fertilizer production, biomass-to-ethanol conversion rates, and energy efficiency in ethanol production have improved the energy balance and GHG emission reduction potential of bioethanol. In the current study, the water, energy, and carbon footprints of bioethanol from corn in the U.S. and sugar cane in Brazil were assessed. The results show that U.S. corn bioethanol has a smaller water footprint (541 L water/L bioethanol) than Brazilian sugar cane bioethanol (1115 L water/L bioethanol). Brazilian sugar cane bioethanol has, however, a better energy balance (17.7 MJ/L bioethanol) and smaller carbon footprint (38.5 g CO2e/MJ) than U.S. bioethanol, which has an energy balance of 11.2 MJ/L bioethanol and carbon footprint of 44.9 g CO2e/MJ. The results show regional differences in the three footprints and highlight the need to take these differences into consideration to understand the implications of biofuel production for local water resources, net energy production, and climate change mitigation

Reply to : On powerful GWAS in admixed populations

Non peer reviewe

2019 Nebraska Water Productivity Report

Nebraska’s agricultural production is diverse and vast, ranking the state fourth in total value of agricultural products in the U.S. The state is a national leader in terms of agricultural production: it is the third largest producer of corn and second largest in cattle production. Nebraska is also the second largest producer of ethanol and distillers’ grains. The production and use of these three commodities are highly interlinked. Corn is a major input in livestock feed and the ethanol industry. Ethanol plants then produce distillers’ grains as a co-product that is also used as livestock feed, thus forming what the Nebraska Corn Board refers to as “Nebraska’s Golden Triangle.” The main objective of the current report is to assess the water productivity of crops and livestock products, and the water, energy and carbon footprint of ethanol produced from corn. The findings show that: • The observed shift to more efficient irrigation systems (eg. changing from gravity to center pivot systems) and setting regulatory limits on pumping for irrigation has helped to reduce the field level irrigation application depth in three Natural Resources Districts (NRDs): Central Platte, Lower Niobrara, and Tri-Basin. The irrigation application rate in the three NRDs studied has dropped on average 20% for cornfields and 8% for soybean fields between 2004 and 2013. • The yield and modeled water productivity (WP) of both irrigated and rainfed corn decreases from eastern to western Nebraska. The drop in irrigated corn yield in western Nebraska is due to a shorter growth season in the west compared to eastern part of the state due to altitude • The modeled water productivity of the two major crops, corn and soybeans, has increased over the years. Between 1990 and 2014, the average WP of corn and soybeans has increased 1.7 and 1.8 times, respectively. These increases closely follow the increase in the crop yields in Nebraska. • There are WP gaps for corn and soybeans that, if targeted investments and improvements are feasible, will help reduce pressure on water resources. • Livestock production (swine and cattle, and eggs) has increased considerably between 1960 and 2016. The increase in livestock production has been accompanied by an increase in animal feed demand. The rate of feed demand has risen more slowly than the rate of increased production, due to increases in livestock productivity. • From 1960 to 2016, the WP of livestock products (beef, pork, chicken meat, turkey meat, milk, and eggs) increased considerably, from 1.8 times for beef to 5.1 times for milk. • Setting benchmarks, estimating the WP gaps, and identifying the critical factors affecting WP are potential future areas of research and investment to enhance the WP of livestock products. • Bioethanol from Nebraska’s corn produces roughly two times more energy output for every unit of fossil fuel input and reduces greenhouse gas (GHG) emission by 53% relative to gasoline