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Both cryosurgery and radiofrequency ablation (RFA) for solid liver tumor treatment are available as minimally invasive procedures that induce changes to the tumor’s thermal environment in order to destroy cancer cells. However, one of the critical factors that impedes cryosurgery and RFA’s successful outcomes is the relatively high recurrence rate caused by the inability to ablate a large damaged tissue zone that envelopes targeted tumors, resulting in therapy failure. To overcome these challenges, a hybrid cryo-RFA system under thermal stress control is proposed in this study. A three-dimensional finite difference analysis is employed to simulate the combined cryosurgery and RF heating protocol. Based on the data acquired from measured experiments, the simulated results derived have demonstrated close agreement with experimental data, with a maximum deviation of 4.8%. We investigated the impacts of varying cryoprobe’s holding temperature and cooling rates on tissue damage. Results have revealed that the tissue damage region is enhanced by properly increasing the cryoprobe’s cooling rate, but the increase of cryoprobe’s cooling rate cannot enlarges the tissue damage area without limit in the freezing process. In addition, the employment of a hybrid cryo-RFA system markedly promotes the destruction of cancer tissue in contrast to conventional stand-alone RF heating or cryosurgery.

Regasification of LNG for combustion in power plants typically employ seawater as a heat carrier in Open-Rack Vaporizers (ORV), causing much of the cold energy to be lost to the ambient. A comprehensive literature review shows that, thus far, no studies have been conducted to simultaneously consider the impacts of the exergy, economy and environment in the optimal design of a hybrid LNG recovery system. This paper aims to address this knowledge gap by establishing a multi-objective optimization model for a novel cascading quad-generation cold energy LNG recovery system. Single- and multi-objective optimizations based on Fuzzy method and Pareto optimal method are carried out on the proposed system to obtain the optimal operating parameters and component sizing, as well as the corresponding performances for each condition. The optimal sizing for each stage is computed for the maximizing of exergy efficiency and CO2 savings rate, and the minimizing of capital cost. The exergy efficiency obtained from the triple-objective optimization yields 12.3% improvement compared to the best result from the single-objective optimization with a 5 kg/s LNG mass flow rate. In addition, when the LNG mass flow is larger than 1 kg/s, the maximized exergy efficiency remains constant (around 0.13) with increasing LNG mass flow rate while the maximized CO2 emission reduction rate and minimized total cost per year increase linearly with the LNG mass flow rate. It has been demonstrated in this work that the system is able to maintain consistency in performance for the optimal design conditions over a wide range of LNG demands and hence good scalability for possible industrial and commercial settings.

Radiofrequency ablation (RFA) for liver tumors is a minimally invasive procedure that uses electrical energy and heat to destroy cancer cells. One of the critical factors that impedes its successful outcome is the thermal heat sink effects from complex vascular systems that give rise to incomplete destruction of the target tumor tissue, resulting in therapy failure. To better understand the thermal influence of the complex vascular system during RFA, this work proposes the employment of two 3D fractal tree-like branched networks to investigate which key factors of the tree-like vascular system impact heating process. A three-dimensional finite difference analysis is employed to simulate the RFA treatment. Based on the data acquired from the measured experiments, the simulated results derived from combining the Pennes bioheat model and the boundary condition-enforced immersed boundary method (IBM) have demonstrated close agreement with experimental data with a maximum discrepancy of ±8.3%. We employed the orthogonal design approach to analyze 3 factors, namely, the blood vessel's volume, the average distance between probe center and the blood vessel system and the number of the selected part's branches at three different levels. Results have revealed that the distance between RFA probe and blood vessel plays a major role during the heating process compared with the other two factors. In addition, both the ablating rates and the volume of damaged tissue are slightly reduced with increasing number of blood vessel branches.

Radiofrequency ablation (RFA) for liver tumors is a minimally invasive procedure that uses electrical energy and heat to destroy cancer cells. One of the critical factors that impedes its successful outcome is the use of inappropriate radiofrequency levels that will not completely destroy the target tumor tissues, resulting in therapy failure. Additionally, the surrounding healthy tissues may suffer from serious damage due to excessive ablation. To address these challenges, this work proposes the employment of injected nanoparticles to thermally promote the ablation efficacy of conventional RFA. A three-dimensional finite difference analysis is employed to simulate the RFA treatment. Based on the data acquired from measured experiments, the simulation results have demonstrated close agreement with experimental data with a maximum discrepancy of within ±8.7%. Several types of nanoparticles were selected to evaluate their influences on liver tissue's thermal and electrical properties. We analysed the effects of nanoparticles on liver RFA via a tumor rending process incorporating several clinically-extracted tumor profiles and vascular systems. Simulations were conducted to explore the temperature difference responses between conventional RFA treatment and one with the inclusion of assisted nanoparticles on several irregularly-shaped tumors. Results have indicated that applying selected nanoparticles with high thermal conductivity and electrical conductivity on the targeted tissue zone promotes heating rate while sustaining a similar ablation zone that experiences lower maximum temperature when compared with the conventional RFA treatment. In sum, incorporating thermally-enhancing nanoparticles promotes heat transfer during the RFA treatment, resulting in improved ablation efficiency.

Radiofrequency ablation (RFA) is becoming an effective treatment method for both primary tumors and tumors that have metastasized. Large tumors in difficult anatomic locations can be treated by RFA technologies. However, constant size and regular shape of damage zones cannot be obtained by recent RFA technologies. The aim of this study is to optimize the stability of RFA treatment by employing a newly proposed bipolar electrode system. A hepatic RFA mathematical model is developed by the finite element method approach. The model is validated with the experimental data. This model is then used to verify the reliability and stability of the proposed electrode system. Simulated results showed the cross section of the ablation zone utilizing designed electrode system approximates a square. In addition, the fraction of the necrosed tissue with this electrode pattern turned out to be larger than the fraction with single-probe RFA techniques. This system demonstrated higher ablation stability even for tissue regions that are close to blood vessels. The proposed electrode system is better suited for matrix-type RFA.

The use of ice as a phase change material (PCM) for such latent thermal energy storage (LTES) systems has been well established in industrial thermal storage. Organic phase-change materials (PCMs) such as paraffin waxes present advantages over ice for LTES systems in commercial air conditioning application due to higher phase-change temperatures and negligible volume expansion. In this study, an encapsulated ice thermal storage (EITS) system was analysed, modelled via COMSOL and validated with operating data. The numerical model is employed to analyse a similar theoretical encapsulated PCM (EPCM) system under similar and altered operating conditions using experimentally-derived thermal properties. Key results from this work revealed that the EPCM system is able to attain higher cold energy storage capacity of up to 3 times that of a reference chilled water tank and 9.37% more than that of the EITS under high flow conditions due to greater degrees of solidification. The effect of heat transfer fluid flowrate on solidification ratio and energy charged is also observed to be more pronounced in EPCM systems as compared to EITS systems.

Cryosurgery is becoming an effective method to treat undesired tumor tissue via the application of extremely low temperature coolant flowing through a probe. To maximize cryoinjury in the targeted tumor region, multiple cryoprobes are simultaneously employed to freeze the surrounding tumor tissues. In order to minimize cryosurgical injury to the surrounding health tissues, the cryoprobe localization for each specific tumor is critical. We developed finite difference analysis to calculate the freezing process during cryosurgery. According to our experimental data, the simulation results from the Pennes equation coupled with immersion boundary method (IBM) are consistent with the experimental data, with a maximum error of ± 8.12 %.We further incorporate a genetic algorithm as a planning tool to address the problem in connection to be interactive positioning of the cryoprobes and the freezing process duration during the pre-operative stage. Several optimization scenarios are judiciously investigated to emphasize different performance variables. Key results have revealed that this computerized approach is highly efficient one for selecting optimized multiple operational parameters.