On the Effectiveness of Temperature-Responsive Protective Fabric Incorporated With Shape Memory Alloy (SMA) Under Radiant Heat Exposure

Abstract

To improve thermal protection of protective clothing, temperature-responsive protective fabrics incorporated with shape memory alloy (SMA) springs varying on four different deformation heights and five types arrangement modes were designed. The thermal protection was investigated under radiant heat exposure of 0.39 cal/cm² s. The results indicated that the air gap between fabric layers produced by SMA springs effectively improved protective performance. The thermal protection of fabrics with different SAM arrangement modes and sizes showed different trends, and the interaction effects of arrangement mode and size were analyzed. Moreover, the optimized arrangement and size of SMA springs were suggested. The regression models were established to assess the relationship between the air gap and thermal protection. This study demonstrated that the combination of flame-resistant fabric with SMA was feasible to develop temperature-responsive protective clothing because it could improve thermal insulating property by producing intelligent air gaps that responded to environment change.

Keywords

air gap shape memory alloy thermal protection thermal protective fabric

In recent years, there has been an increasing demand for thermal-protective clothing (TPC). Personnel such as firefighters and emergency rescuers working in high-temperature conditions usually confront multiple hazards including the impact of physical debris, corrosive chemical liquids, viral infections, and flame, radiation, and heat convection (Holmer, 2006; Sun, Yoo, Zhang, & Pan, 2000). Hence, TPC with excellent thermal-protective performance (TPP) is of great importance to protect the health and safety of personnel in such conditions. To improve the protective performance of TPC, effective strategies are mainly implemented by changing fabric structure, increasing fabric layers, and optimizing fabric combinations. In general, a typical fire-protective fabric system consists of three layers (i.e., a flame-resistant outer shell, a moisture barrier, and a thermal liner; J. Lu, Hong, & Yoon, 2013). However, this type of system is usually heavy and impermeable due to its multiple layers and thickness, which easily limits body movement and also causes high body heat storage (Y. H. Lu, Li, Li, & Song, 2013; Y. Lu, Song, & Wang, 2015). In order to protect the security as well as improve the working efficiency of such personnel, TPC should not only have basic properties such as tear and abrasion resistance but also provide thermal protection and be ergonomically sound. TPC should adapt to the external thermal environment dynamically (i.e., it should provide excellent TPP in an extremely hot environment and decrease the negative impact of fabric thickness in causing physiological burden during human activities; He, Park, Li, & Kim, 2017). Therefore, the development of temperature-responsive protective clothing might provide an effective approach.

Shape memory material (SMM) could undergo significant macroscopic deformation when triggered by an external stimulus such as heat, electricity, light, magnetism, or moisture (Leng, Lan, Liu, & Du, 2011). Two typical SMMs (shape memory alloy [SMA] and shape memory polymer) are widely used in smart textiles (Gök, Bilir, & Gürcüm, 2015). When actuated, they could produce irregular air gaps in the clothing and provide extra thermal protection. Congalton (1999) applied nickel titanium SMA springs with two actuation temperatures (45 °C and 57 °C) into TPC, which was placed between two flame-retardant fabrics. The resulting heat transfer was greatly decreased in the TPC with SMA springs, and the TPC incorporating SMA springs with an actuation temperature of 45 °C showed better TPP. However, the fabric combination in this study does not represent the typical thermal-protective fabric system with two or three layers; thus, the results could not be used to predict the actual TPP of TPC. Hendrickson (2011) used shape memory rings (SMRs) that created 7-mm air gaps in the clothing system when actuated. It was observed that the clothing system with SMR prolonged the rescue time by approximately 30 s. Later, White (2012) found that the TPP was significantly improved when SMRs were stuck on the outer surface of the moisture barrier, and those with an actuation temperature of 45 °C also showed good performance when reducing heat transfer from the atmosphere to body skin. This is similar to Congalton’s (1999) findings. On the basis of Hendrickson’s (2011) study, Yates (2012) constructed a prototype gear with SMRs embedded in the pockets at the shoulder and upper arm. A human test was conducted in a burning room. The results showed the gear with SMRs was more effective at reducing the temperature rise inside clothing and provided a certain degree of protection. G. Park, Chae, and Kim (2012) designed two-way Ni–Ti SMA springs and incorporated them into the thermal liners of firefighters’ turnout gear. They found that the springs increased the protection time by about 30%. M. K. Park, Lee, and Kim (2012) further investigated the attachment of SMA springs to the fabric by four different attachment methods and two different stitching shapes (square and wave). They demonstrated that the attaching methods and stitching shapes had limited impact on thermal protection and found that a wave-type stitch with silicone attachment was an optimum method to adhere the SMA springs to the firefighters’ turnout gear. In recent years, Ma, Wang, Lu, and Dai (2017) examined six arrangements of SMA springs incorporated in clothing fabrics under hot surface contact and found the arrangement has a remarkable impact on the TPP of the fabrics. Further, He, Lu, Wang, and Ma (2018) investigated the TPP of fabrics incorporated with SMA springs of two sizes and six arrangements in two exposure conditions; they demonstrated that the SMA springs could be used to develop intelligent TPC and the arrangement of the SMA springs affects the fabric’s TPP.

Ma, Lu, He, and Dai (2018) demonstrated that the application of SMAs in fabric temperature-responsive protective clothing was effective in improving the TPP of TPC. However, the abovementioned researchers mainly focused on the effect of SMA arrangement on the TPP of TPC, and these SMAs had predetermined specifications. No researcher investigated the effect of a single SMA size or the interaction effect between SMA size and arrangement on the thermal protection of TPC. Investigating these effects is important for realizing the optimized thermal protection of TPC. To fill this gap, the central aim of this study was to explore the relationship between the TPP of TPC and the size and arrangement of the SMAs incorporated as well as the interaction effect between the SMA arrangement and size. Our research findings will be helpful for developing temperature-responsive protective clothing with high thermal protection.

Material and Methods

SMA Springs

The SMA springs were ordered and manufactured by Xi’an Saite Metal Material, China. This type of SMA spring was a copper-based alloy, and the components of the alloy were copper, aluminum, and zinc. The spring diameter was 1.5 mm and the transition temperature (T_trans) was 45 °C. It had two shapes (i.e., temporary shape [T < T_trans] and permanent shape [T > T_trans]; Otsuka & Ren, 2005). When the temperature was lower than T_trans, the temporary shape of the alloy (i.e., a flat coil, shown in Figure 1A) could be maintained. When heated to the T_trans, the temporary shape of the alloy would automatically recover to its original permanent shape, shown in Figure 1B. In this study, SMA springs with four sizes were used (i.e., 8, 16, 24, and 32 mm; Figure 1B). Their weights were 1.1, 1.9, 3.2, and 4.6 g, respectively.

Figure 1.

Different sizes of shape memory alloy springs in (A) temporary shape and (B) permanent shape.

Design of Fabric System With SMA Springs

The protective fabric system consisted of a flame-resistant outer shell, a moisture barrier, and a thermal liner; it was cut into 15 cm × 15 cm. The basic properties of the fabric layers are described in Table 1. The SMA springs were stitched into the external surface of the thermal liner by using para-aramid threads. Four arrangement modes were designed, plus a control (shown in Figure 2): (a) CON—the control group with no spring; (b) Mode 1—one spring was located in the center of the fabric specimen; (c) Mode 2—two springs were positioned diagonally with a distance of 7 cm; (d) Mode 3—three springs were positioned diagonally: one was located in the center and the other two were 5 cm from the center one; and (e) Mode 4—three springs arranged at the vertices of an equilateral triangle with the side length of 6 cm. Configurations of SMA springs with four sizes and four modes are shown in Table 2. To avoid relative movement between each layer, fabric layers were stapled together at diagonal positions.

Figure 2.

Four different arrangement modes of shape memory alloy springs.

Table 1.

Basic Properties of the Testing Fabrics.

Layer	Component	Structural Features	Mass (g/m²)	Thickness (mm)
Outer shell	98% Meta-aramid/2% para-aramid	Twill	186.7	0.41
Moisture barrier	100% Meta-aramid/PTFE film	Water thorn felt with PTFE	106.3	0.69
Thermal liner	100% Meta-aramid	Needle-punched nonwoven with meta-aramid woven face cloth	200.0	2.06

Note. PTFE = polytetrafluoroethylen.

Table 2.

Configurations of SMA Springs With Four Sizes in Four Modes.

Size	Mode 1	Mode 2	Mode 3	Mode 4
8	8-1	8-2	8-3	8-4
16	16-1	16-2	16-3	16-4
24	24-1	24-2	24-3	24-4
32	32-1	32-2	32-3	32-4

Note. SMA = shape memory alloy.

Test Conditions

Precondition

The protective fabric system with SMA springs was preconditioned for at least 24 hr in a standard climatic chamber of 20 ± 2 °C and 65 ± 4% relative humidity prior to tests.

Test apparatus

Statistical reports pinpoint that continuous exposure to a low radiant heat condition took up to 80% of the working time for firefighters and caused a larger number of burn injuries than the conditions of direct contact with hot surface and flash fire (Y. H. Lu, Song, & Li, 2014). Therefore, the TPP tester (Model 701-D-163-1; Precision Products) was used to simulate low radiation exposure (Figure 3), which was in accordance with a previous study by Song et al. (2010). Radiant heat was generated by a bank of nine translucent quartz infrared lamps and placed horizontally beneath a specimen. The radiant heat flux was maintained at 0.39 ± 0.015 cal/cm² s (i.e., 16.4 ± 0.6 kW/m²). The exposure duration was set as 77 s, and the temperature recording was stopped after 150 s. During the test, the external surface of the outer shell was positioned facing the thermal exposure (Barker, Guerth-Schacher, & Grimes, 2006). The experimental data were collected by a temperature acquisition system, including a Type-T thermocouple (Omega Engineering, Norwalk, CT; accuracy: ±0.5 °C) with a wire diameter of 0.274 mm (Omega Engineering; accuracy: 0.5 °C) and a data acquisition system (National Instruments, NI 9213, Austin, TX; Keiser & Rossi, 2008). The detecting point of the thermocouple was placed in the center of the thermal liner’s inner surface. The temperature was measured at a sampling frequency of 0.5 s.

Figure 3.

Radiant heat exposure test.

Evaluation indices

The TPP of the fabric system was evaluated based on temperature histories and the time needed to reach a temperature rise of 24°C (ht24) in accordance with ISO 6942:2002 (International Organization for Standardization, 2002). Additionally, both the temperatures at the end of the 77-s exposure (T₇₇) and the maximum temperature (T_max) were measured.

Statistical analysis

Descriptive statistics (means and standard deviations) were calculated for all dependent variables: ht24, T₇₇, and T_max. One-way analysis of variance (ANOVA) using SPSS Version 20.0 (SPSS Inc., Chicago, IL) was conducted to explore the difference of the indicators due to spring arrangement and size. Post hoc analysis was performed using a least significant difference test to assess the parameters that displayed significant differences in the ANOVA.

Results

The Effect of SMA Arrangement

Figure 4 illustrates the temperature curves of thermal liner’s internal surface in different arrangement modes and sizes. Generally, the temperature exhibited steady growth during the 77-s exposure and continued to increase after the exposure until reaching its maximum value at approximately 90 s. Then, it gradually declined until the end of the test. Further, the temperature change rate of CON was the highest throughout the test, and those of Modes 1 and 3 were the lowest. It is noted that T_max values in Modes 1 and 3 were about 5–20°C lower than those in Modes 2 and 4. Compared with CON, Modes 1 and 3 greatly reduced the temperature at the internal surface of the thermal liner during exposure, reducing the T_max from 125.5 °C to a range of 102.9–56.2 °C.

Figure 4.

Temperature histories with different arrangements of shape memory alloy springs: (A) 8-mm size, (B) 16-mm size, (C) 24-mm size, and (D) 32-mm size.

The data information of the dependent variables (ht24, T₇₇, and T_max) of the fabric assemblies is summarized in Table 3. It was indicated that fabric assembly with SMAs in any arrangement had a significantly higher ht24, but lower T₇₇ and T_max compared with CON (p < .05). Thermal protection time (ht24) and the temperature at the end of 77-s exposure (T₇₇) showed that Modes 1 and 3 presented the maximum performance change, increasing ht24 by 85–304% and decreasing T₇₇ by 37–56% (i.e., from 121.6 °C to a range of 76.9–53.7 °C). The performance of Modes 2 and 4 was inferior to Modes 1 and 3 (i.e., Modes 2 and 4 increased ht24 by 46–90% and reduced T₇₇ by 22–47% compared with CON). No significant difference was observed between Mode 1 and Mode 3 (p < .05), or between Modes 2 and 4.

Table 3.

Thermal Insulating Properties of the Fabric Combinations Incorporated With Different Sizes and Modes of SMA Springs.

Size	Mode	Time to Reach Temperature Rise of 24 °C		Temperature at 77 s		Maximum Temperature
Size	Mode	t₂₄, s (SD)	The Ratio to CON	T₇₇, °C (SD)	The Ratio to CON	T_max, °C (SD)	The Ratio to CON
CON	—	21.1 (2.7)	1	121.6 (10.7)	1	125.5 (11.1)	1
8 mm	1	40.0 (4.6)^ab	1.85	76.9 (8.0)^a	0.63	81.1 (10.4)^a	0.65
	2	31.9 (3.8)^a	1.51	94.4 (8.0)^b	0.78	102.9 (8.1)^b	0.82
	3	39.8 (3.5)^b	1.89	72.6 (5.7)^a	0.60	81.8 (3.9)^a	0.65
	4	36.5 (3.1)^ab	1.73	89.0 (8.6)^ab	0.73	99.8 (4.0)^b	0.80
16 mm	1	43.6 (3.3)^c	2.06	72.8 (1.8)^ab	0.60	77.5 (1.7)^a	0.62
	2	36.0 (1.9)^ab	1.71	82.5 (4.4)^bc	0.68	88.6 (4.8)^b	0.71
	3	42.9 (5.8)^bc	2.03	69.1 (4.9)^a	0.57	72.9 (3.7)^a	0.58
	4	34.0 (4.0)^a	1.61	85.6 (5.9)^c	0.70	92.8 (7.3)^b	0.74
24 mm	1	54.7 (6.4)^b	2.59	60.3 (5.1)^a	0.50	64.6 (6.8)^a	0.51
	2	40.0 (11.6)^a	1.90	71.3 (8.7)^a	0.59	74.6 (8.4)^a	0.59
	3	39.1 (2.5)^ab	1.85	66.9 (5.8)^a	0.55	69.0 (6.8)^a	0.55
	4	39.4 (4.7)^ab	1.86	65.6 (0.6)^a	0.54	69.0 (1.1)^a	0.55
32 mm	1	57.4 (4.5)^b	2.72	55.0 (4.5)^ab	0.45	58.0 (4.9)^ab	0.46
	2	35.3 (5.8)^a	1.67	64.0 (2.9)^bc	0.53	66.3 (3.7)^bc	0.53
	3	64.2 (4.3)^b	3.04	53.7 (2.8)^a	0.44	56.2 (2.3)^a	2.23
	4	30.9 (4.1)^a	1.46	69.5 (1.8)^c	0.57	71.4 (1.2)^c	1.76

Note. SD = standard deviations; t₂₄ = the time to reach the temperature rise of 24 °C; T₇₇ = the temperature at 77 s; T_max = the maximum temperature throughout the test; SMA = shape memory alloy.

^a,b,cEach testing sample with the same superscript letter does not differ significantly from other modes of the same size (p > .05); otherwise, significant differences determined between other modes using least significant difference post hoc tests (p < .05).

The Effect of SMA Spring Size

Results of ht24, T₇₇, and T_max for fabric assemblies with different spring sizes are presented in Figure 5. It can be seen that T₇₇ and T_max were significantly reduced with the increasing SMA size, independent of the SMA arrangement (p < .05). From the data of the three indices, CON showed significant differences compared with others (p < .05). Significant differences in ht24 were observed when configurations 8-1 and 16-1 were compared to configurations 24-1 and 32-1, and when configuration 32-3 was compared to configurations 8-3, 16-3, and 24-3 (p < .05). However, the effect of spring sizes on ht24 was not significantly different between Modes 2 and 4. T₇₇ values observed for the protective fabric systems with 24- and 32-mm SMAs were significantly different from those of 8 and 16 mm (p < .05) in Modes 1, 2, and 4. For Mode 3, the configuration 32-3 showed a significantly higher T₇₇ than other cases. For all arrangement modes, there were no significant differences in ht24 and T₇₇ between fabric systems with 8- and 16-mm SMA springs. The differences between CON and samples incorporated with SMA springs in T₇₇ and T_max increased as the spring size increased. With regard to T_max, the fabric system with 8-mm SMA springs was significantly different from those with 24- and 32-mm SMAs in all arrangement modes and showed a difference from SMAs with 16 mm only in Mode 2. For the size of 16 mm, T_max was different from that of 32 mm in all arrangements but was different from that of 24 mm only in Modes 2 and 4. The difference between specimens with 24 and 32 mm SMA was only observed in Mode 3. The T_max of 32-mm SMA was 11.3–55.1% higher than that of other sizes.

Figure 5.

Comparisons of the thermal-protective performance of the fabric system incorporated with four different sizes of shape memory alloy springs.

The Relationship Between SMA Size and TPP

To further explore the relationship between the SMA size and ht24, T₇₇, and T_max, the fitting analysis is displayed in Figure 6, and the equations are listed in Table 4. Each fitting curve showed high correlations. In Figure 6A, the regression equation for Mode 1 indicated that the ht24 logarithmically increased with the increasing SMA size (R² = .965). However, a fluctuation for Mode 3 occurred, showing a cubic polynomial relationship (R² = .955). The regression analyses for Modes 2 and 4 could not be successfully established (R² < .77). For all arrangement modes, the relationship between SMA size and T₇₇, and that between SMA size and T_max, was successfully established with R² ranging from .897 to .998. T₇₇ and T_max, shown in Figure 6B and 6C, continuously decreased with the increase of SMA size. The temperature curves for Modes 1 and 3 were similar and showed faster decreasing rates than those of Modes 2 and 4 at the beginning. Generally, the TPP was improved with the increase of SMA size, whereas the change trends were nonlinear. The interaction effect between SMA arrangement mode and size was analyzed via a univariate general linear model. The results showed that the influences of SMA arrangement mode and size on the TPP of the fabric system were interactive. These could be confirmed from the variations in effect of SMA arrangement and size shown in “The Effect of SMA Arrangement” and “The Effect of SMA Spring Size” sections.

Figure 6.

Relationships between the shape memory alloy size and (A) t₂₄, (B) T₇₇, and (C) T_max.

Table 4.

The Equations of Fitting Analysis Between the Air Gap Size and t₂₄, T₇₇, and T_max.

Indices	Mode	Equations	Adjusted R²
t ₂₄	1	$t_{24} = - 19.12078 + 20.96488 \times ln (L_{airgap} + 6.87032)$	.96549
t ₂₄	3	$t_{24} = 20.71286 + 4.84866 \times L_{airgap} @^{3} - 0.34172 \times L_{airgap} @^{2} + 0.00726 \times L_{airgap}$	.95546
T ₇₇	1	$T_{77} = 129.83877 - 21.23078 \times ln (L_{airgap} + 1.70971)$	.99832
	2	$T_{77} = 54.25474 + 66.81566 \times exp (- L_{airgap} / 17.26278)$	.99245
	3	$T_{77} = 118.67771 - 17.72814 \times ln (L_{airgap} + 1.40662)$	.99403
	4	$T_{77} = 64.38765 + 56.57294 \times exp (- L_{airgap} / 11.50964)$	.89693
T _max	1	$T_{max} = 141.19142 - 23.42609 \times ln (L_{airgap} + 2.23062)$	.99820
	2	$T_{max} = 38.7255 + 86.54321 \times exp (- L_{airgap} / 27.88306)$	.99785
	3	$T_{max} = 142.19152 - 23.68862 \times ln (L_{airgap} + 2.53019)$	.99746
	4	$T_{max} = 55.73677 + 71.42507 \times exp (- L_{airgap} / 20.54105)$	.90580

Note. L_airgap = air gap size.

Discussion

The temperature curve of CON was significantly higher than those of fabrics incorporated with SMA springs. This was attributed to the air gaps produced by SMA springs during heat exposure. When the SMA spring was activated by the heating source, it recovered its original permanent shape (i.e., changing from a flat coil to a spring), which produced an air layer between fabrics. The heat transfer through the air layer sharply decreased because the heat conductivity of the still air is .035–.047 W/m °C, which is about 1/6 times lower than that of aramid fabric. Therefore, the temperature of the internal surface of the thermal liner was greatly reduced due to the incorporation of SMA springs.

The effect of SMA arrangement mode on ht24, T₇₇, and T_max is shown in Table 3 and Figure 4. Modes 1 and 3 had significantly higher TPP than Modes 2 and 4, and all the fabric systems with SMA springs were superior to CON. This was consistent with He et al.’s (2018) study. In this study, the number of SMA sizes increased from 2 to 4, and the results were more comprehensive. The explanation is that the air gap thickness distribution between the thermal liner and the moisture barrier was different. The air gap formed by Mode 1 was produced in the middle and decreased on the edge. The air gap in Mode 3 looked like a cylinder lying in the fabric along the direction of the spring arrangement because one pair of fabric corners in a diagonal position away from the springs were stapled together as referred to in the “Design of Fabric System with SMA Springs” section. Theoretically, the TPP of Mode 3 was superior to that of Mode 1 because the air gap in Mode 3 was more uniform and stable. However, there was no significant difference between the two modes, which may be attributed to the limitation of the single-point temperature measurement method. Only the temperature in the fabric center was recorded, and we are therefore lacking surface temperature measurements for the whole fabric system. The air gap configuration in Mode 2 was similar to that in Mode 3 but was more uneven because the distance between each of the two springs was 2 cm larger in Mode 2. The air gap in Mode 4 protruded at the edge and decreased in the middle, and thus the temperature at the center was higher, significantly different from the temperature distribution in Modes 1 and 3. The increase of the distance between the two adjacent springs decreased the air gap thickness at the center of the two springs, reducing the thermal protection of the fabric systems. When SMA springs are incorporated in TPC, the regions where SMA springs are inserted and the distribution of SMA springs should be considered.

The performance of 8- and 16-mm SMA springs was significantly different from the 24- and 32-mm springs in any arrangement mode except for Mode 3. In Mode 3 with a uniform air gap, the 32-mm SMA showed a prominent advantage in comparison with other sizes. The difference in TPP between the 8- and 16-mm SMA or between the 24- and 32-mm SMA was not significant. In order to achieve better TPP, the SMA size should be larger than 16 mm. According to the relationship curves, the performance was improved slowly when the SMA size was in the range of 24–32 mm. In some regions of the clothing, increasing the SMA size from 24 to 32 mm provided a slight increase in protective performance but would greatly reduce the wearer’s mobility. Therefore, the design of SMA size in different regions of the garment should be thoroughly considered. For example, at the regions of the upper thigh, abdomen, and shoulder, mobility was a priority during apparel design (i.e., SMA size should not be higher than 24 mm and the distance between springs should be set within 7 cm). Conversely, the regions such as the chest and forearm are directly exposed to ambient thermal hazards, so the size of SMA springs should be increased to 32 mm and the distance should be reduced to approximately 5 cm. However, the SMA springs should not be placed in the joint and mid-back area, where the fabric layers are frequently squeezed.

According to the analysis of the general linear model, the influences of SMA arrangement mode and size on the TPP of fabric systems were interactive. The interaction effect had a remarkable significant impact on the ht24. With the size increase of the SMAs, the effect of arrangement mode on the TPP was also changed. The possible reason is that ht24 of 24 mm was lower than that of 16 mm in Mode 3, and the protection time ht24 for 16 mm was higher than that for 32 mm in Modes 2 and 4. Although the fabric system with larger SMAs displayed lower T₇₇ and T_max, the fabric system with 24-mm SMA was superior to that with 32 mm in Mode 4. The property of Mode 3 should be better than that of Mode 4 on account of the more stable air gap in Mode 3, whereas their differences on protective performance were not significant when the spring size was 24 mm. Therefore, to realize the optimized TPP of the fabric systems, the interaction effect of the arrangement Mode and size of SMAs should be taken into consideration.

The temperatures in Modes 2 and 4 increased rapidly during exposure and then dropped rapidly after the radiant exposure. However, the temperature changes in Modes 1 and 3 were opposite, and the temperatures at the 150-s mark were higher than the former. Air gaps in the fabric system can improve the energy storage within the fabric layer and therefore decrease heat transmission to the skin (Barker, Deaton, & Ross, 2011; Torvi & Dale, 1999). If the thermal insulation is added on the outer shell or the moisture barrier only, it will reduce the energy storage in the thermal liner (He, Chen, Wang, & Li, 2017). As the air gap decreases, the energy storage in the air layer decreases and the thermal energy transferred to skin increases. Thus, the energy storage in the internal surface of thermal liner increases. However, high energy storage has the potential to release more heat after exposure (He, Lu, Chen, & Li, 2017). That was the reason why the temperatures of Modes 2 and 4 soared during the test and slumped after exposure.

Conclusions

In this study, a temperature-responsive fabric incorporated with SMA springs of different modes and sizes was constructed and investigated. The results showed that the air gap in the fabric assembly with three springs positioned diagonally was uniform and stable, so that the TPP was superior compared with other modes. The influence of arrangement mode and size of SMA springs on the TPP of the fabric system was interactive. As the SMA size increased, the effect of arrangement mode on the protective performance also changes. The TPP was greatly improved with the increase in SMA size, whereas the increase rate of TPP decreased. In order to achieve better protective performance, the SMA size should be larger than 16 mm. The research findings of this study were helpful for constructing temperature-responsive protective clothing incorporated with SMAs.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by National Natural Science Foundation of China (Grant Number 51606131), Technology Innovation Project of Key Industries in Suzhou (Grant Number SYG201812), Nantong Municipal Science and Technology Project (Grant Number JC2018039), and Humanity and Social Science Youth Foundation of Ministry of Education of China (Grant Number 18YJC760021).

ORCID iD

Yehu Lu

References

Barker

R. L.

Deaton

A. S.

Ross

K. A.

(2011). Heat transmission and thermal energy storage in firefighter turnout suit materials. Fire Technology, 47, 549–563.

Barker

R. L.

Guerth-Schacher

Grimes

R. V.

(2006). Effects of moisture on the thermal protective performance of firefighter protective clothing in low-level radiant heat exposures. Textile Research Journal, 76, 27–31.

Congalton

(1999). Shape memory alloys for use in thermally activated clothing, protection against flame and heat. Fire and Materials, 23, 223–226.

Gök

M. O.

Bilir

M. Z.

Gürcüm

B. H.

(2015). Shape-memory applications in textile design. Procedia—Social and Behavioral Sciences, 195, 2160–2169.

J. Z.

Chen

Wang

L. C.

(2017). Quantitative assessment of the thermal stored energy in protective clothing under low-level radiant heat exposure. Textile Research Journal, 88, 2867–2879.

J. Z.

Y. H.

Chen

(2017). Investigation of the thermal hazardous effect of protective clothing caused by stored energy discharge. Journal of Hazardous Materials 2017, 338, 76–84.

J. Z.

Y. H.

Wang

L. J.

N. N.

(2018). On the improvement of thermal protection for temperature-responsive protective clothing incorporated with shape memory alloy. Materials, 11, 1932.

J. Z.

Park

Kim

(2017). Physiological and psychological responses while wearing firefighters protective clothing under various ambient conditions. Textile Research Journal, 87, 929–944.

Hendrickson

B. W.

(2011). The impact of a variable air gap on the thermal performance of firefighter protective clothing (Master’s thesis, University of Maryland). Retrieved from http://hdl.handle.net/1903/11591

10.

Holmer

(2006). Protective clothing in hot environments. Industrial Health, 44, 404–413.

11.

International Organization for Standardization. (2002). ISO 6942:2002 (i): Protective clothing—Protection against heat and fire-method of test: Evaluation of materials and material assemblies when exposed to a source of radiant heat. Technical Committee ISO/TC 94 & Technical Committee CEN/TC 162.

12.

Keiser

Rossi

R. M.

(2008). Temperature analysis for the prediction of steam formation and transfer in multilayer thermal protective clothing at low level thermal radiation. Textile Research Journal, 78, 1025–1035.

13.

Leng

J. S.

Lan

Liu

Y. J.

S. Y.

(2011). Shape-memory polymers and their composites: Stimulus methods and applications. Progress in Materials Science, 56, 1077–1135.

14.

Hong

Yoon

(2013). Effect of aerogel on thermal protective performance of fire-fighter clothing. Journal of Fiber Bioengineering & Informatics, 6, 315–324.

15.

Y. H.

Song

G. W.

(2013). The effect of air gaps in moist protective clothing on protection from heat and flame. Journal of Fire Sciences, 31, 99–111.

16.

Y. H.

Song

G. W.

(2014). A novel approach for fit analysis of thermal protective clothing using three-dimensional body scanning. Applied Ergonomics, 45, 1439–1446.

17.

Song

Wang

(2015). Performance study of protective clothing against hot water splashes: From bench scale test to instrumented manikin test. Annals of Occupational Hygiene, 59, 232–242.

18.

N. N.

Y. H.

J. Z.

Dai

H. Q.

(2018). Application of shape memory materials in protective clothing. The Journal of the Textile Institute, 1–9.

19.

N. N.

Wang

L. J.

Y. H.

Dai

H. Q.

(2017). Thermal protection of fireproof fabrics with shape memory alloy springs under hot surface contact. In Li

W. L.

(Eds.), TBIS 2017. Proceedings of 10th Textile Bioengineering and Informatics Symposium (pp. 752–758). Textiles Bioengineering and Informatics Society.

20.

Otsuka

Ren

(2005). Physical metallurgy of Ti-Ni-based shape memory alloys. Progress in Materials Science, 50, 511–678.

21.

Park

Chae

Kim

(2012). Thermal protective performance of fire fighter turnout gear embedded with shape memory alloy thermal lines. In Mäkinen

(Ed.), ECPC 2012. Proceedings of the 5th European Conference on Protective Clothing and NOKOBETEF 10 (p. 97). Aitex Textile Research Institute.

22.

Park

M. K.

Lee

J. Y.

Kim

(2012). Attachment of two-way shape memory alloy onto fabric for mass production of fire fighters’ turnout gear. Journal of the Korean Society of Clothing and Textiles, 36, 382–390.

23.

Song

G. W.

Paskaluk

Sati

Crown

E. M.

Dale

J. D.

Ackerman

(2010). Thermal protective performance of protective clothing used for low radiant heat protection. Textile Research Journal, 81, 311–323.

24.

Sun

G. W.

Yoo

Zhang

Pan

(2000). Radiant protective and transport properties of fabrics used by wildland firefighters. Textile Research Journal, 70, 567–573.

25.

Torvi

D. A.

Dale

J. D.

(1999). Heat transfer in thin fibrous materials under high heat flux. Fire Technology, 35, 210–231.

26.

White

J. P.

(2012). An experimental analysis of firefighter protective clothing: The influences of moisture and a thermally activated expanding air-gap (Master’s thesis, University of Maryland). Retrieved from http://hdl.handle.net/1903/12818

27.

Yates

D. A.

(2012). Design and evaluation of a thermally responsive firefighter turnout coat (Master’s thesis, University of Maryland). Retrieved from http://hdl.handle.net/1903/14763