scholarly journals Fast Adaptive Temperature-Based Re-Optimization Strategies for On-Line Hot Spot Suppression during Locoregional Hyperthermia

Cancers ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 133
Author(s):  
H. Petra Kok ◽  
Johannes Crezee

Background: Experience-based adjustments in phase-amplitude settings are applied to suppress treatment limiting hot spots that occur during locoregional hyperthermia for pelvic tumors. Treatment planning could help to further optimize treatments. The aim of this research was to develop temperature-based re-optimization strategies and compare the predicted effectiveness with clinically applied protocol/experience-based steering. Methods: This study evaluated 22 hot spot suppressions in 16 cervical cancer patients (mean age 67 ± 13 year). As a first step, all potential hot spot locations were represented by a spherical region, with a user-specified diameter. For fast and robust calculations, the hot spot temperature was represented by a user-specified percentage of the voxels with the largest heating potential (HPP). Re-optimization maximized tumor T90, with constraints to suppress the hot spot and avoid any significant increase in other regions. Potential hot spot region diameter and HPP were varied and objective functions with and without penalty terms to prevent and minimize temperature increase at other potential hot spot locations were evaluated. Predicted effectiveness was compared with clinically applied steering results. Results: All strategies showed effective hot spot suppression, without affecting tumor temperatures, similar to clinical steering. To avoid the risk of inducing new hot spots, HPP should not exceed 10%. Adding a penalty term to the objective function to minimize the temperature increase at other potential hot spot locations was most effective. Re-optimization times were typically ~10 s. Conclusion: Fast on-line re-optimization to suppress treatment limiting hot spots seems feasible to match effectiveness of ~30 years clinical experience and will be further evaluated in a clinical setting.

Author(s):  
Horacio Nochetto ◽  
Peng Wang ◽  
Avram Bar-Cohen

Driven by shrinking feature sizes, microprocessor hot spots have emerged as the primary driver for on-chip cooling of today’s IC technologies. Current thermal management technologies offer few choices for such on-chip hot spot remediation. A solid state germanium self-cooling layer, fabricated on top of the silicon chip, is proposed and demonstrated to have great promise for reducing the severity of on-chip hot spots. 3D thermo-electrical coupled simulations are used to investigate the effectiveness of a bi-layer device containing a germanium self-cooling layer above an electrically insulated silicon layer. The parametric variables of applied current, cooler size, silicon percentage, and total die thickness are sequentially optimized for the lowest hot spot temperature compared to a non-self-cooled silicon chip. Results suggest that the localized self-cooling of the germanium layer coupled with the higher thermal conductivity of the silicon chip can significantly reduce the temperature rise resulting from a micro-scaled hot spot.


This paper describes an experimental study of the initiation of solid explosives, and in particular the effect of artificially introducing transient hot spots of known maximum temperature. This was done by adding small foreign particles (or grit) of known melting-point. The minimum transient hot-spot temperature for the initiation of a number of secondary and primary explosives has been determined in this way. It is shown that the melting-point of the grit is the determining factor , and all the grits which sensitize these explosives to initiation either by friction or impact have melting-points above a threshold value which lies between 400 and 550 ° C. Grit particles of lower melting-point do not sensitize the explosives. The same explosives initiated by the adiabatic compression of air required, for initiation, minimum transient temperatures of the same order as the threshold melting-point values. The results provide strong evidence that the initiation of solids as well as of liquids by friction and impact is thermal in origin and is due to the formation of localized hot spots. There is evidence that in the case of the majority of secondary explosives which melt at comparatively low temperatures, intergranular friction is not able to cause explosion and the hot spots must be formed in some other way. With the primary explosives which explode at temperatures below their melting-points, hot spots formed by intergranular friction can be important.


Author(s):  
Zhengang Zhao ◽  
Zhangnan Jiang ◽  
Yang Li ◽  
Chuan Li ◽  
Dacheng Zhang

The temperature of the hot-spots on windings is a crucial factor that can limit the overload capacity of the transformer. Few studies consider the impact of the load on the hot-spot when studying the hot-spot temperature and its location. In this paper, a thermal circuit model based on the thermoelectric analogy method is built to simulate the transformer winding and transformer oil temperature distribution. The hot-spot temperature and its location under different loads are qualitatively analyzed, and the hot-spot location is analyzed and compared to the experimental results. The results show that the hot-spot position on the winding under the rated power appears at 85.88% of the winding height, and the hot-spot position of the winding moves down by 5% in turn at 1.3, 1.48, and 1.73 times the rated power respectively.


2014 ◽  
Vol 521 ◽  
pp. 409-413 ◽  
Author(s):  
Ya Bo Chen ◽  
Yue Sun ◽  
Xu Ri Sun ◽  
Ge Hao Sheng ◽  
Xiu Chen Jiang

The safe operation of power transformers mainly depends on proper functioning of insulation, whose status is revealed by temperatures. Applying ZigBee wireless network, a real-time temperature on-line monitoring and analysis system is developed to view the operation status of underground distribution transformers and process fault diagnosis. Furthermore, using the top-oil and hot-spot temperature calculation method in IEEE Std C57.91-1995, the system can compute a prediction of those temperatures with current load ratio and ambient temperature. System will display early warnings if temperatures are much higher than expected ones, in which way insulation aging can be handled in advance. Insulation fault and big disasters will be prevented.


Author(s):  
Alireza Motieifar ◽  
Cyrus Shafai ◽  
Hassan M. Soliman

The thermal input into high-power Integrated Circuits (IC) can have local peaks or hot spots with heat fluxes far exceeding 100 W/cm2. In this work, the temperature distribution on a microfluidic heatsink has been simulated using the FEM method. The effects of the fluid flow and thickness of the heatsink on the hot spot temperature have been studied. Simulations have been performed for a 1 cm × 1 cm heat sink loaded with 100 W/cm2 heating power, with a 1 mm hot spot of 1000 W/cm2 and a 3 mm hot spot of 500 W/cm2. Heat sinks fabricated from silicon, nickel, and copper are considered. These results show that the effect of increasing the thickness of the heatsink on the peak temperature of the hot spot depends on the solid material and the fluid flow. Simulations showed that the hot spot temperature rise can be about 40% higher if a nickel heat sink is used instead of a copper heat sink.


Author(s):  
Peng Wang ◽  
Avram Bar-Cohen ◽  
Bao Yang ◽  
Gary L. Solbrekken ◽  
Yan Zhang ◽  
...  

Driven by shrinking feature sizes, microprocessor “hot-spots” — with their associated high heat flux and sharp temperature gradients — have emerged as the primary “driver” for on-chip thermal management of today’s IC technology. Solid state thermoelectric micro-coolers offer great promise for reducing the severity of on-chip “hot-spots”, but the theoretical cooling potential of these devices, fabricated on the back of the silicon die in an IC package, has yet to be determined. The results of a three-dimensional electro-thermal finite-element modeling study of such a micro-cooler are presented. Attention is focused on the hot-spot temperature reductions associated with variations in micro-cooler geometry, chip thickness, and chip doping concentration, along with the parasitic Joule heating effects from the electrical contact resistance and current flow through the silicon. The modeling results help to define the optimum solid-state cooling configuration and reveal that, for the conditions examined, nearly 80% of the hot-spot temperature rise of 2.5°C can be removed from a 70μm × 70μm, 680W/cm2 hot-spot on a 50μm thick silicon die with a single micro-cooler.


2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Wataru Nakayama

A system of temperature calculations is developed to study the conditions leading to hot spot occurrence on multicore processor chips. The analysis is performed on a physical model which incorporates certain salient features of multicore processor. The model has active and background cells laid out in a checkered pattern, and the pattern repeats itself in fine grain active cells. The die has a buried dioxide and a wiring layer stacked on the die body, and heat sources are placed at the wiring layer/buried oxide interface. With this model we explore the effects of various parameters on the target spot temperature. The parameters are the die dimensions, the materials' thermal conductivities, the effective heat transfer coefficients on the die surfaces, the power map, and the spatial resolution with which we view the power and temperature distributions on the die. Closed-form analytical solutions are derived and used to examine the roles of these parameters in creating hot spots. The present paper reports the details of mathematical formulations and steps of temperature calculation. The results for a particular example case are included to illustrate what can be learned from the calculations.


Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3561 ◽  
Author(s):  
Kunicki ◽  
Borucki ◽  
Cichoń ◽  
Frymus

A proposal of the dynamic thermal rating (DTR) applied and optimized for low-loaded power transformers equipped with on-line hot-spot (HS) measuring systems is presented in the paper. The proposed method concerns the particular population of mid-voltage (MV) to high-voltage (HV) transformers, a case study of the population of over 1500 units with low average load is analyzed. Three representative real-life working units are selected for the method evaluation and verification. Temperatures used for analysis were measured continuously within two years with 1 h steps. Data from 2016 are used to train selected models based on various machine learning (ML) algorithms. Data from 2017 are used to verify the trained models and to validate the method. Accuracy analysis of all applied ML algorithms is discussed and compared to the conventional thermal model. As a result, the best accuracy of the prediction of HS temperatures is yielded by a generalized linear model (GLM) with mean prediction error below 0.71% for winding HS. The proposed method may be implemented as a part of the technical assessment decision support systems and freely adopted for other electrical power apparatus after relevant data are provided for the learning process and as predictors for trained models.


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