Electronic packaging cabinets simplified modeling, simulation, and experimental validation for systems engineering

SIMULATION ◽  
2022 ◽  
pp. 003754972110699
Author(s):  
José V C Vargas ◽  
Sam Yang ◽  
Juan Carlos Ordonez ◽  
Luiz F Rigatti ◽  
Pedro H R Peixoto ◽  
...  
Keyword(s):  
Heat Source ◽  
Systems Engineering ◽  
Electronic Packaging ◽  
Hot Spot ◽  
Thermal Response ◽  
Power Source ◽  
Junction Temperature ◽  
Variable Loading ◽  
Data Set ◽  
The Impact

A simplified three-dimensional mathematical model for electronic packaging cabinets was derived from physical laws. Tridimensionality resulted from the domain division in volume elements (VEs) with uniform properties, each with one temperature, and empirical and theoretical correlations allowed for modeling their energetic interaction, thus producing ordinary differential equations (ODEs) temperatures versus time system. The cabinet (2048 mm × 1974 mm × 850 mm) thermal response with one heat source was measured. Data set 1 with a 1.6-kW power source was used for model adjustment by solving an inverse problem of parameter estimation (IPPE) having the cabinet internal average air velocities as adjustment parameters. Data set 2 obtained with a 3-kW power source validated model results. The converged mesh had a total of 7500 VE. The steady-state solution took between 16 and 19 s of CPU time to reach convergence and less than 3 min to obtain the 6500-s cabinet dynamic response under variable loading conditions, in an Intel CORE i7 computer. After validation, the model was used to study the impact of heat source height on system thermal response. Fundamentally, a sharp minimum junction temperature Tjct,min = 98.5 °C was obtained in the system hot spot at an optimal heat source height, which was 25.7 °C less than the highest calculated value within the investigated range (0.1 m < zjct < 1.66 m) for the 1.6-kW power setting, which characterizes the novelty of the research, and is worth to be pursued, no matter how complex the actual cabinet design may be.

A Study of Transient Thermal Spreading of VLSI Packaging With Multi Level Scaling

2007 ◽  
Author(s):  
Kazuaki Yazawa ◽  
Tenko Yamashita ◽  
Hideaki Kuroda
Keyword(s):  
Power Consumption ◽  
Hot Spot ◽  
Thermal Response ◽  
Spot Size ◽  
Thermal Interface ◽  
Vlsi Chip ◽  
Expected Performance ◽  
Chip Size ◽  
Transient Thermal ◽  
The Impact

Trend of VLSI chip power consumption sounds switch over from the Moore’s law to more moderate curve by the “multi core processing” paradigm. Many of the recent advanced VLSI chips adopt the multiple processing units since clock enhancement is no longer feasible to gain the expected performance based on realistic range of power consumption. Even though, heat flux may keep increasing by further fine semiconductor process and may keep localizing by further complex logics. In this study, thermal impact of hot spot size relative to chip size or the dimension of heat sink is investigated by analytic modeling as well as numerical analysis. The analytic transient thermal spreading model in a solid with transfer function has already proposed and was validated in our previous work. In this study, we have considered the impact of thermal interface between the heat source and conductive and spreading component to the sink. Thermal response in wide rage of scales is discussed from transistor level to a millimeter scale. Each level of such various sizes can be investigated individually and can be built up with some sort of cascade manner. Based on this model, thermal diffusion in silicon substrate, which has the thermal coupling with spreader and thermal interface, will be discussed for a further fine process generation of the chip. The result implies that passive thermal spreading can be achieving to the limit.

scholarly journals 46 Novel creep area heat source impact on pre-wean mortality occurrence

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 34-35
Author(s):  
Benjamin Smith ◽  
Brett Ramirez ◽  
Laura L Greiner
Keyword(s):  
Heat Source ◽  
Fixed Effects ◽  
Mixed Model ◽  
Random Effect ◽  
Experimental Unit ◽  
Mortality Data ◽  
Accounting System ◽  
Swine Industry ◽  
Data Set ◽  
The Impact

Abstract Pre-wean mortality (PWM) is a multifaceted problem facing the US swine industry. The objective of this study was to compare the occurrence of mortality and age of piglets between a novel heat source (HS; semi-enclosed heated microclimate; SEHM) and a conventional heat lamp setup. This study was conducted in two rooms at a 1,000 head commercial sow farm. Treatments were blocked by sow parity group (SPG; young, prime, and geriatric) over six farrowing cycles. Litters were cross fostered within HS treatment at 1 day of age. PWM, was the experimental unit, data were collected from the farm’s farrowing records and production accounting system. Age of the mortalities was categorized into four phases of lactation (PL) over the 20 d lactation (d0 to d3, d4 to d7, d8 to d11, and d12 to d20). Overall, there were 220 recorded instances of mortality. Data were analyzed in a CRBD using a PROC MIXED model in SAS (v9.4, SAS Inst., Cary, NC) and reported as LSMEANS with standard errors. The model included farrowing cycle as a random effect and the following fixed effects: HS, SPG, PL, HS*SPG, and HS*PL. Overall average PWM was 8.60%±0.80 for SEHM and 10.0%±0.70 for the heat lamps. There was no effect (P &gt;0.05) of HS or HS*PL on PWM occurrence. There were significant effects of SPG (P=0.026), PL (P=0.05), and HS*SPG (P=0.036) on PWM occurrence. These data suggest that the HS type did not have an impact on the mortality rate or the timing of the mortality, indicating the mortalities that occurred had no relationship to HS. A limitation of this data set is the low sample size, thereby limiting the detection ability for this interaction. Further research into the impact of the HS is needed to expand the data set and to explore other popular HS effects on PWM.

Effects of A Rotated Chip Package on Mechanical and Thermal Performances

2003 ◽  
Author(s):  
Henry H. Jung ◽  
Ron Zhang ◽  
Eddie Lee ◽  
Sai Ankireddi
Keyword(s):  
Thermal Analysis ◽  
Mechanical Stress ◽  
Stress Reduction ◽  
Mechanical Design ◽  
Hot Spot ◽  
Junction Temperature ◽  
Design Considerations ◽  
Temperature Performance ◽  
The Impact ◽  
Spot Temperature

In the industry, heatsinks have commonly been oriented on IC packages so that their plan outlines are edge-wise parallel to those of the package. However there are situations where a rotated orientation is preferable, wherein the plan outline of the package is not ‘aligned’ with that of the heatsink assembly — in other words a situation where the heatsink location/orientation remain unchanged while the package itself is rotated in-plane. Mechanical design considerations may drive the need for such a non-traditional orientation, since the rotated package is anticipated to have lower mechanical stress levels in the silicon than the non-rotated one under the same heatsink-induced clamping load. In this study we examine the impact of such package rotation(s) on both the junction temperature performance of CPU packages and the package-level clamp-load induced mechanical stresses. Results show that the stress reduction in the rotated package is in the range of 15% to 60%. The thermal analysis also demonstrates that the effects on the hot spot temperature with 45 degrees rotation is an increase of almost 2°C compared with the non-rotated die case. This increase in junction temperature is expected to be even higher with lower airflow as seen in typical computer systems. Thus it may be inferred that it is important to consider the effects of die rotation on package performances.

Age at Exposure to Parental Suicide and the Subsequent Risk of Suicide in Young People

Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Kuan-Ying Lee ◽  
Chung-Yi Li ◽  
Kun-Chia Chang ◽  
Tsung-Hsueh Lu ◽  
Ying-Yeh Chen
Keyword(s):  
Young People ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Birth Registry ◽  
Data Set ◽  
Parental Suicide ◽  
The Impact ◽  
Age At Exposure

Abstract. Background: We investigated the age at exposure to parental suicide and the risk of subsequent suicide completion in young people. The impact of parental and offspring sex was also examined. Method: Using a cohort study design, we linked Taiwan's Birth Registry (1978–1997) with Taiwan's Death Registry (1985–2009) and identified 40,249 children who had experienced maternal suicide (n = 14,431), paternal suicide (n = 26,887), or the suicide of both parents (n = 281). Each exposed child was matched to 10 children of the same sex and birth year whose parents were still alive. This yielded a total of 398,081 children for our non-exposed cohort. A Cox proportional hazards model was used to compare the suicide risk of the exposed and non-exposed groups. Results: Compared with the non-exposed group, offspring who were exposed to parental suicide were 3.91 times (95% confidence interval [CI] = 3.10–4.92 more likely to die by suicide after adjusting for baseline characteristics. The risk of suicide seemed to be lower in older male offspring (HR = 3.94, 95% CI = 2.57–6.06), but higher in older female offspring (HR = 5.30, 95% CI = 3.05–9.22). Stratified analyses based on parental sex revealed similar patterns as the combined analysis. Limitations: As only register-­based data were used, we were not able to explore the impact of variables not contained in the data set, such as the role of mental illness. Conclusion: Our findings suggest a prominent elevation in the risk of suicide among offspring who lost their parents to suicide. The risk elevation differed according to the sex of the afflicted offspring as well as to their age at exposure.

State Medical Boards' Perceptions of a Minimum Data Set and Current Practices for Collecting Physician Information

2013 ◽  
Vol 99 (4) ◽  
pp. 40-45 ◽  
Author(s):  
Aaron Young ◽  
Philip Davignon ◽  
Margaret B. Hansen ◽  
Mark A. Eggen
Keyword(s):  
Media Coverage ◽  
The United States ◽  
Minimum Data Set ◽  
Direct Patient Care ◽  
Physician Workforce ◽  
Data Set ◽  
Minimum Data ◽  
State Medical Boards ◽  
The Impact ◽  
Current Practices

ABSTRACT Recent media coverage has focused on the supply of physicians in the United States, especially with the impact of a growing physician shortage and the Affordable Care Act. State medical boards and other entities maintain data on physician licensure and discipline, as well as some biographical data describing their physician populations. However, there are gaps of workforce information in these sources. The Federation of State Medical Boards' (FSMB) Census of Licensed Physicians and the AMA Masterfile, for example, offer valuable information, but they provide a limited picture of the physician workforce. Furthermore, they are unable to shed light on some of the nuances in physician availability, such as how much time physicians spend providing direct patient care. In response to these gaps, policymakers and regulators have in recent years discussed the creation of a physician minimum data set (MDS), which would be gathered periodically and would provide key physician workforce information. While proponents of an MDS believe it would provide benefits to a variety of stakeholders, an effort has not been attempted to determine whether state medical boards think it is important to collect physician workforce data and if they currently collect workforce information from licensed physicians. To learn more, the FSMB sent surveys to the executive directors at state medical boards to determine their perceptions of collecting workforce data and current practices regarding their collection of such data. The purpose of this article is to convey results from this effort. Survey findings indicate that the vast majority of boards view physician workforce information as valuable in the determination of health care needs within their state, and that various boards are already collecting some data elements. Analysis of the data confirms the potential benefits of a physician minimum data set (MDS) and why state medical boards are in a unique position to collect MDS information from physicians.

IR Thermography for Temperature Measurements and Fault Location on AlGaN/GaN HEMTs and MMICs

2015 ◽  
Author(s):  
Lény Baczkowski ◽  
Franck Vouzelaud ◽  
Dominique Carisetti ◽  
Nicolas Sarazin ◽  
Jean-Claude Clément ◽  
...  
Keyword(s):  
Fault Location ◽  
Hot Spot ◽  
Life Time ◽  
High Electron Mobility Transistors ◽  
Junction Temperature ◽  
High Electron ◽  
Ir Thermography ◽  
Operating Life ◽  
Gan Hemt ◽  
Electron Mobility Transistors

Abstract This paper shows a specific approach based on infrared (IR) thermography to face the challenging aspects of thermal measurement, mapping, and failure analysis on AlGaN/GaN high electron-mobility transistors (HEMTs) and MMICs. In the first part of this paper, IR thermography is used for the temperature measurement. Results are compared with 3D thermal simulations (ANSYS) to validate the thermal model of an 8x125pm AIGaN/GaN HEMT on SiC substrate. Measurements at different baseplate temperature are also performed to highlight the non-linearity of the thermal properties of materials. Then, correlations between the junction temperature and the life time are also discussed. In the second part, IR thermography is used for hot spot detection. The interest of the system for defect localization on AIGaN/GaN HEMT technology is presented through two case studies: a high temperature operating life test and a temperature humidity bias test.

The Impact of Green Labels on U.S. Hotel Net Operating Income: Operating Statements Analyses

2019 ◽  
Vol 11 (1) ◽  
pp. 156-173
Author(s):  
Spenser Robinson ◽  
A.J. Singh
Keyword(s):  
Environmental Design ◽  
Green Buildings ◽  
Small Sample ◽  
Sample Survey ◽  
Data Set ◽  
Operating Income ◽  
Energy Star ◽  
The Impact ◽  
Industry Professionals

This paper shows Leadership in Energy and Environmental Design (LEED) certified hospitality properties exhibit increased expenses and earn lower net operating income (NOI) than non-certified buildings. ENERGY STAR certified properties demonstrate lower overall expenses than non-certified buildings with statistically neutral NOI effects. Using a custom sample of all green buildings and their competitive data set as of 2013 provided by Smith Travel Research (STR), the paper documents potential reasons for this result including increased operational expenses, potential confusion with certified and registered LEED projects in the data, and qualitative input. The qualitative input comes from a small sample survey of five industry professionals. The paper provides one of the only analyses on operating efficiencies with LEED and ENERGY STAR hospitality properties.

Does Tax Increment Financing Pass the “But-for” Test in Missouri?

2019 ◽  
Vol 33 (3) ◽  
pp. 187-202
Author(s):  
Ahmed Rachid El-Khattabi ◽  
T. William Lester
Keyword(s):  
Economic Development ◽  
Kansas City ◽  
Time Series Data ◽  
Local Level ◽  
Conclusive Evidence ◽  
Series Data ◽  
Tax Increment Financing ◽  
Data Set ◽  
Development Indicators ◽  
The Impact

The use of tax increment financing (TIF) remains a popular, yet highly controversial, tool among policy makers in their efforts to promote economic development. This study conducts a comprehensive assessment of the effectiveness of Missouri’s TIF program, specifically in Kansas City and St. Louis, in creating economic opportunities. We build a time-series data set starting 1990 through 2012 of detailed employment levels, establishment counts, and sales at the census block-group level to run a set of difference-in-differences with matching estimates for the impact of TIF at the local level. Although we analyze the impact of TIF on a wide set of indicators and across various industry sectors, we find no conclusive evidence that the TIF program in either city has a causal impact on key economic development indicators.

Evaluation of the Aging Behavior of High Density Polyethylene in Thermal Oxidative Environment by Principal Component Analysis

2017 ◽  
Vol 727 ◽  
pp. 447-449 ◽  
Author(s):  
Jun Dai ◽  
Hua Yan ◽  
Jian Jian Yang ◽  
Jun Jun Guo
Keyword(s):  
Principal Component Analysis ◽  
Impact Strength ◽  
High Density Polyethylene ◽  
Tensile Modulus ◽  
Principal Component ◽  
Component Analysis ◽  
High Density ◽  
Aging Behavior ◽  
Data Set ◽  
The Impact

To evaluate the aging behavior of high density polyethylene (HDPE) under an artificial accelerated environment, principal component analysis (PCA) was used to establish a non-dimensional expression Z from a data set of multiple degradation parameters of HDPE. In this study, HDPE samples were exposed to the accelerated thermal oxidative environment for different time intervals up to 64 days. The results showed that the combined evaluating parameter Z was characterized by three-stage changes. The combined evaluating parameter Z increased quickly in the first 16 days of exposure and then leveled off. After 40 days, it began to increase again. Among the 10 degradation parameters, branching degree, carbonyl index and hydroxyl index are strongly associated. The tensile modulus is highly correlated with the impact strength. The tensile strength, tensile modulus and impact strength are negatively correlated with the crystallinity.

scholarly journals Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yahya Albalawi ◽  
Jim Buckley ◽  
Nikola S. Nikolov
Keyword(s):  
Social Media ◽  
Deep Learning ◽  
Comprehensive Evaluation ◽  
Classification Problem ◽  
Data Sets ◽  
Word Embeddings ◽  
Data Set ◽  
Lower Accuracy ◽  
Health Related ◽  
The Impact

AbstractThis paper presents a comprehensive evaluation of data pre-processing and word embedding techniques in the context of Arabic document classification in the domain of health-related communication on social media. We evaluate 26 text pre-processings applied to Arabic tweets within the process of training a classifier to identify health-related tweets. For this task we use the (traditional) machine learning classifiers KNN, SVM, Multinomial NB and Logistic Regression. Furthermore, we report experimental results with the deep learning architectures BLSTM and CNN for the same text classification problem. Since word embeddings are more typically used as the input layer in deep networks, in the deep learning experiments we evaluate several state-of-the-art pre-trained word embeddings with the same text pre-processing applied. To achieve these goals, we use two data sets: one for both training and testing, and another for testing the generality of our models only. Our results point to the conclusion that only four out of the 26 pre-processings improve the classification accuracy significantly. For the first data set of Arabic tweets, we found that Mazajak CBOW pre-trained word embeddings as the input to a BLSTM deep network led to the most accurate classifier with F1 score of 89.7%. For the second data set, Mazajak Skip-Gram pre-trained word embeddings as the input to BLSTM led to the most accurate model with F1 score of 75.2% and accuracy of 90.7% compared to F1 score of 90.8% achieved by Mazajak CBOW for the same architecture but with lower accuracy of 70.89%. Our results also show that the performance of the best of the traditional classifier we trained is comparable to the deep learning methods on the first dataset, but significantly worse on the second dataset.

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