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Fabrics with photothermal conversion functions were developed based on the introduction of shape stable composite phase change materials (CPCMs).

Acidified single-walled carbon nanotubes (SWCNTs) were selected as support material to prepare CPCMs with n-octadecane to improve the thermal conductivity and shape stability. The CPCMs were finished onto the surface of cotton fabric through the coating and screen-printing method. The chemical properties of CPCMs were characterized by Fourier transform infrared spectrometer, XRD and differential scanning calorimetry (DSC). The shape stability and thermal conductivity were also evaluated. In addition, the photothermal conversion and temperature-regulating performance of the finished fabrics were analyzed.

When the addition amount of acidified SWCNTs are 14% to the mass of n-octadecane, the best shape stability of CPCMs is obtained. DSC analysis shows that the latent heat energy storage of CPCMs is as high as 183.1 J/g. The thermal conductivity is increased by 84.4% compared with that of n-octadecane. The temperature-regulating fabrics coated with CPCMs have good photothermal conversion properties.

CPCMs with high latent heat properties are applied to the fabric surface through screen printing technology, which not only gives the fabric the photothermal conversion performance but also reflects the design of personalized patterns.

CPCMs and polydimethylsiloxane (PDMS) are mixed to make printing paste and printed cotton fabric with temperature-regulating functional is developed.

SWCNTs and n-octadecane are composited to prepare CPCMs with excellent thermal properties, which can be mixed with PDMS to make printing paste without adding other pastes. The fabric is screen-printed to obtain a personalized pattern and can be given a thermoregulatory function.

Purpose – The purpose of this research is to synthesize modified thermoplastic sago starch (TPS) through in-situ mechanism by reacting sago starch with diphenylmethanediisocyanate (MDI) and castor oil simultaneously, resulting in a more homogenous and finer-sized polyurethane prepolymer (PUP).

Design/Methodology/Approach – The methods used were Thermal Gravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC) for thermal characterization and stability of PUP, modified TPS non-extracted and extracted with toluene and water.

Findings – TGA test results presented shows that PUP begins to decompose thermally at a temperature of 300–500 °C. Weight loss occurs rapidly between these temperatures and is completely discharged at a temperature of 500°C, which is called weight loss transition.

Research Limitations/Implications – When extracted with toluene and a water solvent, the melting point and latent heat of fusion slightly decreased; however, it is still higher than the original value of sago. In terms of thermal stability, modified TPS decomposes and loses weight at 150–200 °C in small quantities, continues with weight loss rapidly, and is completely discharged at 500°C. The thermal stability is considered high; thus, modified TPS application can be varied.

Practical Implications – DSC analysis and TGA shows that modified TPS has good thermal characteristics and thermal stability. Modified TPS has a melting point of 104.69°C, and the latent heat of fusion (ΔH) is 234.27 J/g. This value is close to the PUP melting point and latent heat of fusion, which reveals the formation of cross-link between the starch and PUP.

The purpose of this paper is to identify the impact of traditionally unmonitored energy sources and sinks on assessment of the as-built thermal performance of occupied homes. The analysis aims to demonstrate the potential scale of uncertainties introduced in a heat balance estimation of the heat transfer coefficient (HTC) when using in-use monitored data.

Energy flows for two UK homes – one a 1930s dwelling with high heat loss, the second a higher-performing 2014-built home – are predicted using the UK Government’s standard assessment procedure (SAP) and visualised using Sankey diagrams. Selected modelled energy flows are used as inputs in a quasi-steady state heat balance to calculate in-use HTCs as if from measured data sets gathered in occupied homes. The estimated in-use HTCs are compared against SAP-calculated values to illustrate the impact of including or omitting various heat sources and sinks.

The results demonstrate that for dwellings with low heat loss, the increased proportion of heating demand met by unmetered internal and solar gains informs a greater sensitivity of a heat balance estimation of the HTC to their omission. While simple quasi-steady state heat balance methods may be appropriate for dwellings with very high heat loss, alternative approaches are likely to be required for those with lower heat loss.

A need to understand the impacts of unmetered heat flows on the accuracy with which a building’s thermal performance may be inferred from in-use monitored data is identified: this paper illustrates the scale of these impacts for two homes at opposite ends of the energy performance scale.

It is of great significance to study the influence of subgrade filling on permafrost temperature field in permafrost area for the smooth construction and safe operation of railway.

The paper builds up the model for the hydrothermal coupling calculation of permafrost using finite element software COMSOL to study how permafrost temperature field changes in the short term after subgrade filling, on which basis it proposes the method of calculation for the concave distortion of freezing front in the subgrade-covered area.

The results show that the freezing front below the subgrade center sinks due to the thermal effect of subgrade filling, which will trigger hydrothermal erosion in case of sufficient moisture inflows, leading to the thawing settlement or the cracking of the subgrade, etc. The heat output of soil will be hindered the most in case of July filling, in which case the sinking and the distortion of the freezing front is found to be the most severe, which the recovery of the permafrost temperature field, the slowest, constituting the most unfavorable working condition. The concave distortion of the freezing front in the subgrade area increases with the increase in temperature difference between the filler and ground surface, the subgrade height, the subgrade width and the volumetric thermal capacity of filler, while decreases with the increase of the thermal conductivity of filler. Therefore, the filler chose for engineering project shall be of small volumetric thermal capacity, low initial temperature and high thermal conductivity whenever possible.

The concave distortion of the freezing front under different working conditions at different times after filling can be calculated using the method proposed.

This study aims to simulate the dendritic growth in Stokes flow by iteratively coupling a domain and boundary type meshless method.

A preconditioned phase-field model for dendritic solidification of a pure supercooled melt is solved by the strong-form space-time adaptive approach based on dynamic quadtree domain decomposition. The domain-type space discretisation relies on monomial augmented polyharmonic splines interpolation. The forward Euler scheme is used for time evolution. The boundary-type meshless method solves the Stokes flow around the dendrite based on the collocation of the moving and fixed flow boundaries with the regularised Stokes flow fundamental solution. Both approaches are iteratively coupled at the moving solid–liquid interface. The solution procedure ensures computationally efficient and accurate calculations. The novel approach is numerically implemented for a 2D case.

The solution procedure reflects the advantages of both meshless methods. Domain one is not sensitive to the dendrite orientation and boundary one reduces the dimensionality of the flow field solution. The procedure results agree well with the reference results obtained by the classical numerical methods. Directions for selecting the appropriate free parameters which yield the highest accuracy and computational efficiency are presented.

A combination of boundary- and domain-type meshless methods is used to simulate dendritic solidification with the influence of fluid flow efficiently.

This paper aims to study the impacts of groundwater seepage on artificial freezing process of gravel strata, the temperature field characteristics of the strata, and the strata process, closure time and thickness evolution mechanism of the frozen wall.

In this paper several laboratory model tests were conducted, considering different groundwater seepage rate.

The results show that there is a significant coupling effect between the cold diffusion of artificial freezing pipes and groundwater seepage; when there is no seepage, temperature fields upstream and downstream of the gravel strata are symmetrically distributed, and the thickness of the frozen soil column/frozen wall is consistent during artificial freezing; groundwater seepage causes significant asymmetry in the temperature fields upstream and downstream of the gravel strata, and the greater the seepage rate, the more obvious the asymmetry; the frozen wall closure time increases linearly with the increase in the groundwater seepage rate, and specifically, the time length under seepage rate of 5.00 m d⁻¹ is 3.2 times longer than that under no seepage; due to the erosion from groundwater seepage, the thickness of the upstream frozen wall decreases linearly with the seepage velocity, while that of the downstream frozen wall increases linearly, resulting in a saddle-shaped frozen wall.

The research results are beneficial to the optimum design and risk control of artificial freezing process in gravel strata.

In the field of heritage science, especially applied to buildings and artefacts made by organic hygroscopic materials, analyzing the microclimate has always been of extreme importance. In particular, in many cases, the knowledge of the outdoor/indoor microclimate may support the decision process in conservation and preservation matters of historic buildings. This knowledge is often gained by implementing long and time-consuming monitoring campaigns that allow collecting atmospheric and climatic data.

Sometimes the collected time series may be corrupted, incomplete and/or subjected to the sensors' errors because of the remoteness of the historic building location, the natural aging of the sensor or the lack of a continuous check of the data downloading process. For this reason, in this work, an innovative approach about reconstructing the indoor microclimate into heritage buildings, just knowing the outdoor one, is proposed. This methodology is based on using machine learning tools known as variational auto encoders (VAEs), that are able to reconstruct time series and/or to fill data gaps.

The proposed approach is implemented using data collected in Ringebu Stave Church, a Norwegian medieval wooden heritage building. Reconstructing a realistic time series, for the vast majority of the year period, of the natural internal climate of the Church has been successfully implemented.

The novelty of this work is discussed in the framework of the existing literature. The work explores the potentials of machine learning tools compared to traditional ones, providing a method that is able to reliably fill missing data in time series.