Thermal Conductivity Distribution Research Articles

Evolution of impact-generated hydrothermal systems in basaltic targets on Earth and implications for habitats on Mars

Impact-generated hydrothermal systems are a potential habitat for life on Earth and other planetary bodies. The ubiquity of impact craters on Mars makes them of particular interest for the search for life on this planet although their viability as a habitat is not well understood. To better understand such systems, two analogue impact structures on Earth were investigated, as their dominantly basaltic target rock makes them similar to impact structures in the Martian crust: the Vista Alegre and Vargeão Dome impact structures in Brazil.The goals of this paper are to 1) better understand the Vista Alegre and Vargeão Dome impact structures, and 2) understand how impact-generated hydrothermal systems on Earth can be compared with similar systems on Mars. To enable comparison, the software HYDROTHERM is used to reconstruct the hydrothermal evolution of both impact systems on Earth. Permeability, porosity, thermal conductivity, and initial temperature distributions are varied to simulate slow--, medium-, and fast-cooling models. The medium cooling rate models are then adapted to Martian conditions and scaled to 1×, 2×, 4×, and 8× the size on Earth, also adapting the impact energy and initial heat distribution, to check the comparability using similar target rocks. Finally, target rocks are changed to a basaltic composition only, to check how a lower-permeability Martian surface composition would affect the hydrothermal system.The models indicate between 150 and 650 thousand years (ka) of hydrothermal activity for both the Vista Alegre and Vargeão Dome impact structures. Due to the limited availability of water in the initial, high-temperature situation in the crater centre, water flux first increases and then decreases, although after 650 kyr the water flux towards the crater centre remains active in Vargeão Dome only. This sustained water flux is likely related to the low relative pressure in the crater centre due to the lack of overlying rock in comparison to outside the crater, as well as the direct connection of an underlying sandstone aquifer with high-permeability, fractured basalt in the centre of the structure.The Martian models with the same lithologies as on Earth show overall lower water flux and contain permafrost, which prevents the water flux within the aquifer from outside the crater towards the crater centre as seen in Vargeão Dome. The cooling times increase with scaling from 1× to 8× the size to ~0.2 and 5 Myr, respectively. With only basalts in the target, cooling times reach ~0.2 to 9 Myr. However, in that case, the water flow only remains active for up to the first Myr, and a minimum crater diameter of approximately 40 km is needed to achieve surface water fluxes close to those in Vargeão Dome and Vista Alegre.Below the Martian surface, hydrothermal system activity can persist for millions of years, providing potential for supporting life. Unfortunately, these parts of the system are currently unreachable for both sampling and spectroscopic techniques, and the short lifetime and low water fluxes at the surface related to the permafrost layers do not favour impact-generated hydrothermal systems on present-day Mars as targets for the search for life. However, these systems are highly dependent on the rock types and related permeabilities and could have provided habitats before 3.5 Ga, when the planet was warmer and liquid water was present at the surface.

Highly Sensitive Weaving Sensor of Hybrid Graphene Nanoribbons and Carbon Nanotubes for Enhanced Pressure Sensing Function.

Carbon nanotubes (CNTs) hold great promise in next-generation sensors because of their remarkable physical properties. Yet, maintaining precise stacking configurations of CNTs to make full use of their remarkable properties is challenging because of their susceptibility to spontaneous reconstruction. Inspired by the weaving technology, we propose a CNT-graphene nanoribbon hybrid woven model that can maintain the specific structure of CNTs to achieve their elaborately designed function. In this study, comprehensive molecular dynamics simulations are carried out to investigate the thermal stability of the CNT-graphene hybrid woven model, as well as their potential for pressure sensing applications by utilizing the unique response of thermal transport to mechanical deformation at heterojunctions. The thermal stability is sensitive to the size of the graphene nanoribbon, and the woven structure remains stable from 200-500 K when its width is greater than 2.0 nm. Moreover, it is exciting that the sensors are effective at predicting the shapes of externally loaded objects through the analysis of the thermal conductivity distribution, which can be derived from the relationship between the thermal conduction and the pressure. Our findings shed light on the bottom-up functional design of nanomaterials and expand wider applications of high-performance nanosensors in other related fields.

Mechanical and thermal transport in nanoporous graphene-like BC6N

This work analyzes the thermal transport (TT) and mechanical properties (MP) of nanoporous graphene-like BC6N monolayer utilizing non-equilibrium molecular dynamics (NEMD) and molecular dynamic (MD) simulations. Herein, the heat transfer and mechanical of nanoporous graphene-like BC6N membrane with various circle-pore size defects are systematically reviewed and numerically examined. The results show that the BC6N sheet has a balance on mechanical properties in two directions under biaxial tension as changing pore size from D = 2.0 to D = 7.0 nm. Young's modulus and ultimate strength of BC6N monolayer with a circle pore decrease when the pore size increases. The trending laws are also shown to predict the mechanical parameters of the porous BC6N sheet. Besides, the thermal conductivity (TC) of the monolayer BC6N with a smaller pore size is much higher than that of the sample with a bigger pore size due to higher energy loss. Changing pore size can adjust the TC and 2D temperature distribution around the circle-pore. Furthermore, the pristine BC6N TC is more heightened than the defective ones. The study results confirm that 2D-BC6N has outstanding optical, electronic, thermal transport, and mechanical characteristics. It is particularly inspiring for further experimental and theoretical works that advance different technological applications, such as gas sensors, nanoelectronics, and optoelectronic devices. It helps for real-time monitoring, which is critical to improving safety and efficiency in marine and air transportation infrastructure. Keywords: 2D-BC6N, mechanical, thermal transport, energy.

Physics mechanisms underlying the optimization of coherent heat transfer across width-modulated nanowaveguides with calculations and machine learning

Optimization of heat transfer at the nanoscale is necessary for efficient modern technology applications in nanoelectronics, energy conversion, and quantum technologies. In such applications, phonons dominate thermal transport and optimal performance requires minimum phonon conduction. Coherent phonon conduction is minimized by maximum disorder in the aperiodic modulation profile of width-modulated nanowaveguides, according to a physics rule. It is minimized for moderate disorder against physics intuition in composite nanostructures. Such counter behaviors call for a better understanding of the optimization of phonon transport in non-uniform nanostructures. We have explored mechanisms underlying the optimization of width-modulated nanowaveguides with calculations and machine learning, and we report on generic behavior. We show that the distribution of the thermal conductance among the aperiodic width-modulation configurations is controlled by the modulation degree irrespective of choices of constituent material, width-modulation-geometry, and composition constraints. The efficiency of Bayesian optimization is evaluated against increasing temperature and sample size. It is found that it decreases with increasing temperature due to thermal broadening of the thermal conductance distribution. It shows weak dependence on temperature in samples with high discreteness in the distribution spectrum. Our work provides new physics insight and indicates research pathways to optimize heat transfer in non-uniform nanostructures.

The impact of soil layering and groundwater flow on energy pile thermal performance

Shallow geothermal energy pile systems have emerged as cost-effective and low-carbon alternatives for heating and cooling buildings, compared to traditional air-conditioning systems. Geothermal applications have been researched extensively in recent years under the assumption of ground homogeneity, and the effect of ground stratification remains mostly unexplored. To investigate this, a 3D finite element numerical model is developed and validated against laboratory-scale experimental data, to study the transient diffusion-convection heat transfer linked with Darcy groundwater flow around energy piles in multi-layered lithology. The model is used to undertake long-term assessments under balanced and unbalanced thermal loads to evaluate the thermal effects of soil layering and discrepancies against commonly assumed equivalent homogeneous stratum, for soil profiles with different thermal conductivity distributions. The groundwater flow effect at various depths and seepage velocities on the thermal performance of the energy pile is investigated as well. Results demonstrate the need to account for the spatial variability in thermal properties, particularly for unbalanced thermal loading scenarios. The thermal yield can be underestimated by up to 19.6 % due to an inaccuracy of 48.2 % in the accumulated temperature after 25-year of operation with respect to an equivalent homogeneous ground with depth-weighted average thermal conductivity. This discrepancy grows as the contrast between layers increases. An empirical derived formula is presented and tested, presenting a correction to the effective thermal conductivity of the layered systems in this study that considers the thermal contribution of the ground beneath the pile. Groundwater seepage is shown to have a positive impact on the heat exchanger efficiency, and in the layered geology the efficiency under-estimation becomes more critical at low to moderate Darcy velocities, if neglected or inaccurately measured. These findings contribute to a broader understanding of energy piles and can assist engineers and practitioners in optimising energy geo-structure design, boosting the technology’s viability.

A new channel structure for strengthening heat transfer of SCO2 printed circuit heat exchanger (PCHE): variable sectional semicircular channel

In this paper, a mathematical and physical model is established to study the convective heat transfer performance of supercritical carbon dioxide (SCO2) in three kinds of horizontal semicircular channels (uniform cross-sectional channel, diverging and converging channels). The accuracy of the numerical model is verified by comparing with the experimental data. The computational results demonstrate that the converging channel can strengthen heat transfer effectively compared with the uniform cross-sectional channel under the same heat transfer area. In the range of calculated working conditions, the use of a converging channel resulted in a maximum improvement of 42.26% in the heat transfer performance of SCO2. However, the diverging channel deteriorates the heat transfer. It is discovered that the improvement of the field coordination of SCO2 in the converging channel is one of the main reasons for its enhanced heat transfer. In addition, the different distribution of turbulent kinetic energy and thermal conductivity are also an important factor affecting the heat transfer performance of SCO2 in different channels. Finally, we propose a new heat transfer correlation of the SCO2 cooling process in the horizontal semicircular converging channel. Compared with the five selected correlations, the new correlation has the best prediction accuracy, and its mean absolute relative error (MARE) and root mean square error (RMSE) are 9.49% and 10.6%, respectively. Our work will provide new insights and theoretical guidance for the design and optimization of coolers in SCO2 Brayton cycle system.

Multi-source directional heat conduction method based on coordinate transformation

Based on the optical transformation theory, the formal invariance of the heat conduction equation was used to realize the transformation of constitutive parameters of heat conducting materials through coordinate transformation, so as to control the distribution of heat flow in physical space. In addition, based on the research on the control method of heat flow propagation path, a multi-heat source directional heat conduction method with complex boundary was studied for the case where the object is affected by a variety of internal and external heat sources, and the temperature field is uneven, resulting in irregular deformation. Based on translation transformation and compression transformations, the thermal conductivity distribution of the material was derived for the directional heat conduction structure. And the controllable propagation of heat flow from high temperature region to low temperature region was realized. By analyzing three distributions of multiple heat sources, applicable directional heat conduction structures with multiple sources and complex boundaries were designed to realize passive control of temperature field. The performance of directional heat conduction structures in transient state was analyzed by Comsol software simulation, where the direction of the heat flow is observed through the temperature cloud. Then, from the comparison graph of the average temperature of different sides of the heat conduction structure after 60 min, it can be concluded that the difference between the average temperature of different areas decreases, and the temperature field of the structure becomes more uniform.

A 3D thermal conductivity prediction method for deep strata based on temperature field estimation

Accurate predictions of earth’s interior thermal conductivity are essential for interpreting the mechanisms involved in geothermal systems and delineating geothermal resource targets. Existing thermal conductivity prediction methods, which typically involve measurements of rock samples and predictions based on geophysical well logging, cannot accurately predict regional thermal conductivity distributions. We develop a 3D thermal conductivity prediction based on temperature field estimation. First, the finite-element method is used for temperature forward modeling. Subsequently, the inexact Gauss-Newton method is implemented in the prediction algorithm. Synthetic studies indicate that the method can recover the true model well. The subsurface temperature distribution of the Xiong’an New Area is predicted using the coefficient correction method of the optimal temperature. Next, we obtain the 3D distribution of thermal conductivity of deep formation in the Xiong’an New Area with the predicted temperature field. The distribution of terrestrial heat flow also is estimated. In addition, the law of thermal accumulation of strata at different depths is analyzed, and the internal relation among resistivity, temperature, and thermal conductivity is studied. Thus, the 3D thermal conductivity prediction method provides the theoretical basis for interpreting mechanisms for the origin of geothermal systems and heat accumulation patterns. It could have significant utility for the analysis of geothermal fields and the sustainable development and use of geothermal resources.

Inclusión de técnicas de sísmica de refracción en la definición del entorno geológico con fines de aprovechamiento geotérmico

Given the growing importance of geothermal energy in the decarbonization of the energy sector, the application of appropriate methodologies that contribute to a greater knowledge of the resource is considered convenient. In this sense, refraction seismic techniques have proven to be a potential tool to predict the thermal behavior of the subsoil in locations where it is intended to implement a shallow geothermal system. From thermal conductivity measurements on samples with different degrees of compaction and consolidation, and from the propagation speeds of the P waves, a correlation pattern is developed that in turn allows obtaining 2D sections of the average thermal conductivity distribution in depth. The methodology developed shows that it is possible to estimate the evolution of the thermal conductivity parameter of the ground and thus guarantee an adequate design of the well field and the future correct operation of the geothermal system (providing the correct drilling length which would be underestimated by 30% with the standard thermal conductivity values).

Finite time thermodynamic optimization for performance of absorption energy storage systems

Absorption energy storage (AES) has attracted worldwide attention due to the high energy storage density and environmental friendliness. To optimize the performance of the AES system, a finite time thermodynamic (FTT) model considering some influencing factors such as time, heat transfer area, heat transfer temperature difference, internal friction and dissipation has been developed in this paper. A new concept of ratio of charging and discharging time is proposed. The general relation of the energy storage efficiency, energy storage rate and energy release rate are induced based on FTT analysis. The distribution of the total thermal conductivity was optimized under the condition of a certain total thermal conductivity and the optimized maximum cooldown release rate has been increased by 14%. The optimal operating conditions of the AES system are obtained. Furthermore, the influences of the internal irreversibility, ratio of charging and discharging time and heat source temperatures on the performance of the AES system are analyzed. The research results can provide theoretical basis and guidance for the AES system design and optimization.

Multifactor analysis of heat extraction performance of coaxial heat exchanger applied to hot dry rock resources exploration: A case study in matouying uplift, Tangshan, China

To obtain an excellent heat exchange effect, it is necessary to optimize the technical processes of single-well coaxial heat exchange. Based on numerical simulation and field investigation, this study shows that a high inlet temperature can significantly improve the outlet temperature while a low inlet temperature can obtain a high heat extraction power. The outlet temperature and heat extraction power show a positive correlation binomial relation with the inlet flow rate, the thermal conductivity of cement, the thermal conductivity of reservoir and the borehole diameter, which exhibit linear negative and positive correlation relationships with the thermal conductivity of inner tube and geothermal gradient. The inlet flow rate, geothermal gradient and thermal conductivity of the inner tube are the most significant factors, followed by the thermal conductivity of reservoir and the borehole diameter, while the inlet temperature and thermal conductivity of cement are the insignificant factors. It is recommended to select the reservoirs with high geothermal gradient, good thermal conductivity and wide stable distribution, develop fixing well cement with high thermal conductivity and inner pipe materials with excellent insulation performance, reduce the inlet temperature, increase the inlet flow rate of working fluid and expand the well diameter while considering costs.

A Database of Snow on Sea Ice in the Central Arctic Collected during the MOSAiC expedition

Snow plays an essential role in the Arctic as the interface between the sea ice and the atmosphere. Optical properties, thermal conductivity and mass distribution are critical to understanding the complex Arctic sea ice system’s energy balance and mass distribution. By conducting measurements from October 2019 to September 2020 on the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we have produced a dataset capturing the year-long evolution of the physical properties of the snow and surface scattering layer, a highly porous surface layer on Arctic sea ice that evolves due to preferential melt at the ice grain boundaries. The dataset includes measurements of snow during MOSAiC. Measurements included profiles of depth, density, temperature, snow water equivalent, penetration resistance, stable water isotope, salinity and microcomputer tomography samples. Most snowpit sites were visited and measured weekly to capture the temporal evolution of the physical properties of snow. The compiled dataset includes 576 snowpits and describes snow conditions during the MOSAiC expedition.

Estimation method of layered ground thermal conductivity for U-tube BHE based on the quasi-3D model

The distribution of ground thermal conductivity (λs) is a significant consideration for the design of ground source heat pump systems. This paper proposed a new method to estimate the layered λs for U-tube borehole heat exchanger (BHE) using particle swarm optimization (PSO) and distributed thermal response test (DTRT) data. Firstly, a quasi-3D heat transfer model considering geothermal gradient for U-tube BHE had been built to simulate fluid temperature profiles. And the experiment in DTRT was performed using a 45 m sandbox. Then, the layered λs were estimated through PSO and DTRT data based on the established model. The results showed that the convergent λs distribution could be reliably obtained by short-term DTRT. Furthermore, the estimation results are independent of the number of layers and data points. The mean difference in λs distribution between 9 layers and 45 layers is 0.007 W/(m∙K) and the layered λs also could be obtained when the number of layers is more than the number of temperature data points, and the root mean square error between 30 and 220 points is less than 0.3 W/(m∙K).

A generalized Benders decomposition-based algorithm for heat conduction optimization and inverse design

Heat conduction optimization benefits many important applications and attracts researchers’ interest unceasingly. Here we present an alternative heat conduction optimization algorithm on the basis of generalized Benders decomposition technique. In this algorithm, the heat conduction optimization problem is first decomposed to a subproblem and a master problem. The subproblem calculates the temperature field with the given thermal conductivity distribution, updates the upper boundary of objective, and constructs an optimality cut at the current point. The master problem updates the lower boundary of objective from solving the programming problem formed by all optimality cuts generated. The subproblem and master problem are solved alternately, the two boundaries approach mutually, and the optimal solution can be reached. The proposed algorithm is validated by applying it on the classic “volume-to-point” problem. Results show that the average and maximum temperature in the domain can be effectively reduced. It is further extended to the topology optimization to obtain discrete material distribution, and numerical studies are also conducted for validation. Finally, the inverse design of thermal cloak is studied by using the proposed algorithm, and square and circular thermal cloaks are numerically designed and verified. All cases studied demonstrate the efficacy and flexibility of the proposed algorithm.

An effective method for hot spot temperature optimization in heat conduction problem

Heat conduction problem for the optimization of thermal conductivity distribution is gaining considerable concerns in electronics cooling. Previous studies usually adopted optimization criteria to solve this problem. However, it still remains a big challenge for minimization of hot spot temperature, which is a core issue for electronics cooling. In this study, an iterative method based on a novel criterion is developed to minimize the hot spot temperature of customized regions in heat conduction problems. The optimization criterion for minimizing the hot spot temperature is derived using variational principle, which reveals that the optimization mechanism is the synergy of temperature gradient field and multiplier gradient field. An iterative method based on this criterion is developed to adjust the thermal conductivity field for minimization of hot spot temperature. The volume-to-point (VP) heat conduction problem is introduced to validate the proposed method. The results show that the proposed method reduces the hot spot temperature rise in customized regions by 44 %–47 % compared with those with uniform thermal conductivity distribution. Moreover, the developed criterion is also adopted in an allocation and reallocation method for the VP problems with discrete thermal conductivities, reducing the hot spot temperature rise by 88% ∼ 89%.

Development of a hybrid model for fuel performance analysis of spherical fuel elements under normal conditions

The spherical fuel element (SFE) dispersed with many tri-isotropic fuel (TRISO) particles has been primarily employed in the high-temperature gas-cooled reactor. Owing to the complex structure of SFE, behaviors will be evolved for both TRISO particles and the fuel matrix with the increasing burnup. To evaluate the fuel performance of SFE, the homogenization method has been conventionally adopted for SFE scale modeling, and dispersed TRISO particles are analyzed subsequently with fixed temperature boundary conditions. However, owing to the varying properties of TRISO particles under reactor operation, the homogenization models dedicated to certain circumstances can hardly reflect the properties evolution of TRISO with high fidelity, which may lead to uncertainties in analysis results. To this end, a hybrid model, namely the conventional homogenization model informed by the lower scale model online, has been developed in this paper, which may increase modeling fidelity for both SFE and particles. Specifically, property models for the TRISO particle and graphite matrix have been implemented in COMSOL. Subsequently, based on the linking of COMSOL and MATLAB, the hybrid model for SFE analysis was established. Through the hybrid model, the temperature field and stress distribution of TRISO, the evolution of effective properties, and the thermal and mechanical state of the SFE were obtained and analyzed. The results show that within the scope of this paper, the central temperature of TRISO in the innermost region rises with the increasing burnup for the decreasing thermal conductivity of materials, and the peak value is about 1324 K, which is about 60 K higher than that in the outermost region. The difference in the maximum plenum pressure is more than 5 MPa among TRISO particles, which is mainly caused by the variations in CO production. Consequently, the hoop stress of SiC in the outermost region is slightly elevated. The distribution of effective thermal conductivity (ETC) for TRISO is nearly 4.3 W/(m·K) at the beginning of life (BOL), while it was reduced to 3.6 W/(m·K) at the end of life (EOL). There are marginal variations along the radial direction for the ETC of TRISO. Meanwhile, the ETC of SFE decreases from about 21 W/(m·K) for fresh fuel to 13 W/(m·K) for spent fuel. The predicted effective elastic modulus and coefficient of thermal expansion of SFE increase gradually versus time. The former is caused by the densification of pyrolytic carbon, and the latter is mainly determined by the high volume fraction of matrix and the changes of CTE for pyrolytic carbon. In addition, the comparison in the temperature field between the proposed model and the Differential Effective Material Theory (D-EMT) model may further demonstrate the feasibility and effectiveness of the hybrid model.

Thermal Contact Conductance Estimation on Irregular Interfaces Using the Reciprocity Functional Method

The Reciprocity Functional method, associated to the Classic Integral Transform Technique, has been successfully applied, obtaining analytical solutions for the inverse heat transfer problem that seeks to estimate the thermal contact conductance (TCC) distribution on the interface of a body composed of two materials. Yet, the theoretical development upon which this approach is based is not limited to the need of this interface to have a regular format. This work proposes to extend the method, thus obtaining an analytical development for the estimation of the TCC distribution on interfaces which are not necessarily regular. Several test problems were solved using the techniques described in this work, leading to very good results, with low CPU time usage by the computational implementation. The stability of the method was also verified, via a Monte Carlo analysis considering uncertainties in geometrical and thermophysical properties. The method presented good estimates even when noises were present in the measured temperatures, thermal conductivities, and geometrical dimensions.

Simultaneous density and thermal conductivity depth profile reconstructions from noised thermal-wave amplitude and phase data using a combined integral-equation and imperialist competitive algorithm method

An efficient new thermal-wave inverse-problem approach based on an integral-equation boundary-value method coupled with an imperialist competitive algorithm was developed. The methodology was successfully applied to simultaneously reconstruct density and thermal conductivity depth profiles in a sintered powder metallurgy sample from an industrial automotive manufacturer with a surface layer of higher density than the bulk. The density and thermal conductivity depth profiles were validated independently using the manufacturer's data and in-house temperature and porosity measurements. The present non-destructive inverse problem approach represents a generalized formalism to thermal-wave reconstruction of dual depth profiles using frequency scan data measured from the interrogated surface. From a fundamental viewpoint, the method adds significant insights into the relationship between thermal conductivity and density distributions in inhomogeneous solids.

Clogging detection and productive layers identification along boreholes using Active Distributed Temperature Sensing

Fiber-Optic Active Distributed Temperature Sensing (FO-ADTS) experiments were performed on an Aquifer Thermal Energy Storage system (ATES) site located on the university campus of Bordeaux, France. The experiments consisted in heating the steel core of the FO cable while monitoring the rate of temperature increase during the heating periods. The changes in temperature, that were monitored through time at every depth under various hydraulic conditions and in different boreholes, were used to evaluate both aquifer properties and wells conditions. A first ADTS experiment was conducted under cross borehole configuration using a pumping well and a monitoring well separated by a distance of 8.5 meters. Then, to check the reciprocity of the results, a second experiment was conducted by switching the monitoring and the pumping well. The results obtained through the use of analytical solutions for reproducing and interpreting the data lead to the following conclusions: (i) ADTS can be used to estimate both thermal conductivity and Darcy velocity distribution along boreholes, crucial properties for ATES performance. (ii) The proposed method is a promising tool to detect clogging locations in the boreholes when it occurs. This can be of great practical interest to maintain systems performance, since, once FO cables deployed, experiments could be easily repeated without opening boreholes and stop the system operation.

Recycled waste glass usage for construction materials

Recycling glass waste obtained from different industries is an issue in today’s economy. One of the ways of recycling is to produce lightweight ceramic by applying glass waste, clay, and gasifier as raw materials. The present research has been devoted to the evaluation of the influences of different clays extracted from two Latvian quarries (Lielauce un Samini) on the properties of lightweight ceramics. The main criteria of applicated clay as raw materials for producing lightweight ceramic are the following: saturation of SiO2 should be a maximum of 70% and Al2O3 minimum of 12%. The aim of the present research was to elaborate a composition for producing glass ceramic from glass waste with minimum energy consumption with a gasifier. The most important properties of the final product are thermal conductivity, compression strength, volume density, size, granulometry, and pore distribution. Two parameters of them, compression strength and volume density have been tested and analysed in the present research framework. Burning time is one more important additional parameter, which has been considered evaluating the properties of the final product. The obtained volume density is in the range of 226.75 kg/m3 to 475.78 kg/m3 depending on the composition.