Evaluation method and program for building material and the like

Abstract

To provide a method capable of properly evaluating light reflection performance of an object.SOLUTION: The present invention relates to a method that includes processing to acquire a function representing light reflection performance of an object and determination processing to determine whether the object is suitable as a building material based on the function.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a method and a program for evaluating building materials and the like. [Background technology]

[0002] As a conventional technique, a device for measuring the illuminance and the like of lighting is used to ensure the appropriate use of lighting (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2006-302517 A [Non-patent literature]

[0004] [Non-Patent Document 1] Kunio Matsuura, Yoshiaki Kamitani: Mathematical Modeling of Reflection Directivity Characteristics for Lighting Calculation, Research Report of Kinki Branch of the Architectural Institute of Japan, pp.33-36, 1990 [Non-Patent Document 2] K. Torrance and E. Sparrow, Theory for off-specular reflection from roughened surfaces, Journal of Optical Society of America, 57 (1967) 1105-1114, https: / / doi.org / 10.1364 / JOSA.57.001105 [Non-Patent Document 3] RL Cook and KE Torrance, A Reflectance Model for Computer Graphics, ACM SIGGRAPH Computer Graphics, 15 (1981) 307-316, https: / / doi.org / 10.1145 / 965161.806819 [Non-Patent Document 4] Kunio Matsuura, Yoshiaki Kamitani: Measurement of Reflection Directional Characteristics of Building Materials Using Polarized Light, Journal of the Architectural Institute of Japan, Planning and Planning Journal, No. 388, pp. 15-22, June 1988 https: / / doi.org / 10.3130 / aijax.388.0_15 [Non-Patent Document 5] Shuko Yabe, Naoya Hara, Kazunori Harada: Simple estimation of directional reflection characteristics of building materials using easily measurable physical properties, Journal of Environmental Engineering, Architectural Institute of Japan, Vol. 84, No. 758, pp. 377-384, 2019.4, https: / / doi.org / 10.3130 / aije.84.377 [Non-Patent Document 6] Sho Fujita, Shuko Yabe, Kazunori Harada, Daisaku Nii: Estimation of Reflectance Characteristics Using Surface Properties of Building Materials, Abstracts of Academic Lectures at the Architectural Institute of Japan Annual Meeting (Kanto), Environmental Engineering I, pp.469-470, 2020 / 9 Summary of the Invention [Problem to be solved by the invention]

[0005] Conventionally, it has been difficult to appropriately evaluate light reflected from building materials, etc. [Means for solving the problem]

[0006] In consideration of the above problems, one aspect of the present invention provides a method including a process for acquiring a reflection characteristic function of light by an object, and a judgment process for determining the suitability of the object as a building material based on the reflection characteristic function.

[0007] In addition, as one aspect, the present invention provides an apparatus or a program for executing the above-mentioned evaluation method. Effect of the Invention

[0008] According to the present invention, it is possible to provide an evaluation method capable of appropriately evaluating the light reflectance performance of an object. [Brief description of the drawings]

[0009] [Figure 1] 3 is a flowchart of an evaluation method in the first embodiment. [Diagram 2] (a) A diagram showing the definitions of the angle of incidence and the angle of reflection, and (b) a schematic diagram of a measuring device used to measure reflected light. [Diagram 3] This is an equation for the reflection characteristic function. [Figure 4] 13 is a graph showing the BRDF of each sample when (a) the incident angle is 45 degrees and (b) the incident angle is 60 degrees. [Diagram 5] 13 is a flowchart of an evaluation method according to a second embodiment. [Figure 6] 13 is a flowchart of an evaluation method according to a third embodiment. [Figure 7] 13 is a graph showing the BRDF maximum and the standard deviation of the inclination angle of the subfacets for each sample. [Figure 8] 13 is a formula showing the standard deviation of the inclination angle of the small element surface. [Figure 9] 1 is a flow chart illustrating an embodiment of a final selection. [Figure 10] FIG. 1 is a block diagram of a computer system. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] First Embodiment The evaluation method according to the first embodiment of the present invention will be described below with reference to the accompanying drawings. The evaluation method according to the first embodiment is carried out according to the flow chart in FIG.

[0011] First, in step S1, the reflection directional characteristics of a sample are measured. In this embodiment, the sample is assumed to be a building material used for interior and exterior decoration such as a roof, a wall, a floor, etc. Note that various objects other than building materials can be used as the sample.

[0012] A possible method for measuring the reflection directional characteristics is to use a measuring device 1, as shown in Fig. 2. The measuring device 1 includes a light source 11 and a luminance meter 12. The light source 11 emits parallel light, for example a xenon lamp whose spectral distribution of visible light is close to that of sunlight, and includes an illuminance meter 11A for correcting output fluctuations during measurement. The light source 11 irradiates the sample with incident light, and the luminance meter 12 measures the luminance of the reflected light from the sample.

[0013] 2, the angles of the light source 11 and the luminance meter 12 with respect to the sample can be changed. This allows the incident angle of the incident light with respect to the sample and the reflection angle of the reflected light to be changed to angles desired by the measurer.

[0014] In step S1, multiple measurements are performed while sequentially changing the angle of incidence and the angle of reflection. As a result of the measurements, the illuminance of the incident light on the sample surface, the angle of incidence, and the brightness of the reflected light for the angle of reflection are recorded as the reflection directional characteristics of the sample.

[0015] In step S2, a bidirectional reflectance distribution function (BRDF) equation (equation (1) in Fig. 3) is estimated based on the measured reflective directional characteristics. If the incident light is assumed to be direct sunlight with the same direct illuminance on the normal plane, the reflectance characteristic function ρ shown in equation (2) in Fig. 3 may be estimated instead of the BRDF.

[0016] Both BRDF and ρ are understood as functions that indicate the reflectance characteristics of the target sample, as shown in each formula. Various formulas for BRDF and ρ have been proposed, and in addition to formulas (1) and (2), formula (3) (Non-Patent Document 1) and formulas according to Non-Patent Documents 2 and 3 have been proposed. Parameter estimation can be performed by detailed measurements using polarized light (Non-Patent Document 4), by simple estimation from the measured values ​​of the spectral diffuse reflectance and reflective directional characteristics that can be measured by a spectrophotometer or the like (Non-Patent Document 5), or by simple estimation by on-site measurements (Non-Patent Document 6).

[0017] In step S3, the reflection directional characteristics for each incident angle and reflection angle are graphed. Figure 4 is an example of a BRDF graph, showing the BRDF values ​​for multiple samples A and D for each reflection angle when the incident angle is 45 degrees (Figure (a)) and when the incident angle is 60 degrees (Figure (b)).

[0018] In the BRDF graphs of samples A and D, the points where the BRDF is maximum can be confirmed. Since the maximum value of the BRDF correlates with the maximum luminance relative to the illuminance on the sample surface, samples with a large BRDF tend to have a large maximum luminance of reflected light. In Figure 4(a), the maximum BRDF value of sample D is indicated by an arrow extending in the radial direction of the graph.

[0019] In addition, the spread of the BRDF can be confirmed for each sample A and D. In Fig. 4(a), as a concrete example, the spread of the BRDF for sample D is indicated by the arrow extending in the circumferential direction of the graph.

[0020] The spread of BRDF and ρ, which are functions that indicate the reflectance characteristics, corresponds to the spread of the distribution of reflected light. The spread of the distribution of reflected light is visually perceived as the size of the light source to the observer of the object that is reflecting the light. The larger the light source occupies in the field of view, the more likely the observer is to feel glare.

[0021] In the next step S4, an appropriate sample is selected. To be more specific, when BRDF is used as a function indicating the reflection characteristics, a sample is selected that has a small maximum BRDF value, i.e., a small maximum brightness, and a small BRDF spread, i.e., a small distribution of reflected light, under any incident angle condition. To be more specific using the example of FIG. 4(a), among samples A and D, sample C has the smallest maximum BRDF value, and the distribution of reflected light is also smallest in sample C. Therefore, sample C is selected as the optimal one.

[0022] In addition, samples may be selected based only on the maximum value of the BRDF, or based only on the spread of the distribution of reflected light. For example, if there is no significant difference in the spread of the distribution of reflected light between multiple samples, a sample with a small maximum value of the BRDF may be selected. Also, if there is no significant difference in the maximum value of the BRDF between multiple samples, a sample with the smallest spread of the distribution of reflected light may be selected. In addition, in FIG. 2, the illuminance of the sample due to the set incident light, the angle of incidence, the angle of incidence, and the azimuth of reflection may be recorded as the reflection directional characteristics of the sample.

[0023] <Second embodiment> The evaluation method according to the second embodiment is executed according to the flow of Fig. 5. Note that steps S1 and S2 are the same processes as steps S1 and S2 in the first embodiment, and therefore their explanation will be omitted.

[0024] In step S23, the maximum values ​​of functions indicating reflection characteristics such as BRDF and ρ for each incidence angle are compared between multiple samples. For example, the BRDFs of multiple samples are compared for incidence angles of 45 degrees and 60 degrees, and if there is a sample with the smallest maximum BRDF value at both incidence angles (S24: YES), the sample with the smallest maximum BRDF value is selected (S25).

[0025] If the sample with the smallest BRDF maximum value differs depending on the incidence angle, or if it is considered that there is no significant difference between the samples in terms of the BRDF maximum value (S24: NO), the standard deviations of the inclination angles of the minor surface areas of the samples are compared (S26). Note that the samples to be compared may be only those samples with the smallest BRDF maximum value at any incidence angle. Also, the samples to be compared may be only those samples with no significant difference in terms of the BRDF maximum value.

[0026] Specifically, in step S26, the standard deviations of the inclination angles of the subsurfaces of the samples are compared. The standard deviation is calculated based on the measured values ​​of the skin reflection component, as shown in FIG. 8. The standard deviation of the inclination angles of the subsurfaces of the sample correlates with the spread of the distribution of the reflected light. If the maximum BRDF is approximately the same, the larger the standard deviation, the greater the spread of the distribution of the reflected light. In other words, if the maximum BRDF is approximately the same, the larger the standard deviation, the larger the light source of the reflected light will be perceived as to be to the observer of the sample.

[0027] If step S26 has been carried out, then in step S25, the sample with the smallest standard deviation is selected.

[0028] As an example, a graph comparing the standard deviations of the tilt angles for samples A and D is shown in Fig. 7. As shown in Fig. 7, the sample with the smallest BRDF maximum value differs depending on the incident angle (S24: NO), and since sample B has the smallest standard deviation, sample B is selected (S25).

[0029] <Third embodiment> The evaluation method according to the third embodiment is executed according to the flow of Fig. 6. Note that steps S1 and S2 are the same processes as steps S1 and S2 in the first and second embodiments, and therefore a description thereof will be omitted.

[0030] In steps S33 and S34, the maximum values ​​of the reflection characteristic functions for each incident angle are compared between the multiple samples. Specifically, the reflection characteristic functions of the multiple samples are compared for multiple incident angles, and if there is a sample with the largest maximum value of the function indicating the reflection characteristics at all incident angles (S34: YES), that sample is excluded from the selection (S35).

[0031] If multiple samples remain to be selected (S35A: YES), the process returns to step S34, and the processes from S34 onward are executed again. In this way, samples that show large values ​​for the maximum value of the function indicating the reflection characteristics at all angles of incidence are gradually removed from the selection candidates.

[0032] If only one sample remains to be considered for selection (S35A: NO), the sample remaining as the reference sample is finally selected (S37).

[0033] As an example, we will use the graph in Figure 7, which compares the standard deviations of the tilt angles for samples A and D. In the graph in Figure 7, sample A has the largest BRDF maximum value at any incident angle, so it is excluded from the selection.

[0034] In step S34, if there is no sample with the largest maximum value of the function indicating the reflectance characteristics at any incidence angle (S34: NO), the inclination angles of the subsurfaces are compared between the samples remaining as candidates for selection (S36). The specific content is the same as in step S26, and the standard deviations of the inclination angles of the subsurfaces of the samples are compared (FIG. 8). As a result, in step S37, the sample with the largest standard deviation is excluded from the selection candidates. Note that the samples to be compared in step S36 may be only those samples with the smallest BRDF maximum value at any incidence angle. Also, the samples to be compared may be only those samples with no significant difference in the maximum BRDF value.

[0035] To explain using the example of Fig. 7, among samples B, C, and D that are compared in step S36, sample D has the largest standard deviation. Therefore, sample D is excluded from the selection candidates. As a result, samples B and C are extracted as selection candidates (S37).

[0036] In step S37, only sample B with the smallest standard deviation may be extracted as a selection target. Also, if it is considered that there is no significant difference in the standard deviation, a sample may be extracted taking into consideration the smallness of the BRDF maximum value.

[0037] <Implementation of final selection> In the first to third embodiments, there are cases where multiple samples remain as selection candidates, such as when there is no difference or a large difference in the maximum value of the function indicating the reflection characteristics or the standard deviation of the inclination angle of the minor surface. Even when one sample remains as a selection candidate, there are cases where a final confirmation is required as to whether it is suitable as a material to be used. In such cases, the process shown in the flow of FIG. 9 is carried out as the final selection.

[0038] In step S41, a lighting environment simulation is performed. In this lighting environment simulation, a function indicating the reflection characteristics of the sample is set as a physical property value of the reflection of the surface. For example, if the sample is a building material, a building using the sample as an exterior material or the like is modeled, and then the lighting environment simulation is performed.

[0039] In step S42, the luminance distribution of the reflective surface as viewed from the observation point is calculated for each season or year. When the sample is an exterior material, a window or the like in a building near a building using that exterior material is set as the observation point.

[0040] Next, based on the luminance distribution calculated in step S42, indices such as DGP (Daylight Glare Probability) and PGSV (Predicted Glare Sensation Vote) are calculated for each season or year (S43).

[0041] Based on the index calculated in step S43, a sample having the best index value is selected (S44), or a sample having an index value equal to or less than a predetermined threshold value is selected.

[0042] (Devices, programs) Each of the above-mentioned embodiments can be automatically, easily and quickly executed by configuring it as a program that can function on a computer and running it on a computer. For example, as shown in the block diagram of Fig. 10, a computer system C can be configured that includes a storage device 40 that stores a program P and a processing device 30 that includes a computer, and can communicate with each other, and the computer system C can be made to execute the above-mentioned method. In this case, the processing device 30 executes at least a part of the processes S1-S4, S23-S26, S33-S37, and S41-S44 according to the instructions of the started program P.

[0043] <Effects> In each of the above embodiments, the following aspects are disclosed.

[0044] (Mode 1) A process (S2) is executed to obtain a function indicating the light reflection characteristics of an object (corresponding to a sample in each embodiment), and a judgment process (S4, S25, S37) is executed to judge the suitability of using the object based on the function indicating the reflection characteristics.

[0045] In the above configuration, the reflection characteristics of an object can be quantitatively evaluated using a function indicating the reflection characteristics, so that the suitability of the object for use can be appropriately evaluated.

[0046] (Aspect 2) The method of aspect 1 further includes a process (S1) of measuring a reflective directional characteristic of the object, and a function indicative of the reflective characteristic is obtained based on the measured reflective directional characteristic (S2).

[0047] With the above configuration, it is possible to quantitatively evaluate the reflection characteristics of an object based on the reflection directional characteristics, so that the suitability of the object for use can be appropriately evaluated.

[0048] (Embodiment 3) In embodiment 1 or 2, the judgment process includes a process (S4, S25, S37) of judging suitability based on the maximum value of a function indicating the reflection characteristic.

[0049] In the above configuration, since the maximum value of the function indicating the reflection characteristics is used, it is possible to quantitatively grasp the maximum luminance of the light reflected by the object.

[0050] (Aspect 4) In any of aspects 1 to 3, the judgment process includes a process (S3, S26, S36) of obtaining the spread of the distribution of the reflected light based on a function indicating the reflection characteristics, and a process (S4, S25, S37) of judging the suitability based on the distribution.

[0051] With the above configuration, the size of the light source as seen by a person viewing the reflected light from the object can be quantitatively evaluated, and therefore the characteristics of the object can be appropriately determined.

[0052] (Aspect 5) In any of aspects 1 to 4, the determination process further includes a process of calculating a standard deviation of the tilt angles on the minor surface of the object (S26, S36) and a process of grasping the spread of the distribution based on the standard deviation (S26, S36).

[0053] In the above configuration, the standard deviation can be used to grasp the spread of the distribution of the reflected light, which means that the size of the light source as seen by a person viewing the reflected light of an object can be quantitatively evaluated.

[0054] (Aspect 6) In any of aspects 1 to 5, the judgment process includes a process of plotting a function indicating the reflection characteristics on a graph (S3, S23, S33), and a process of judging suitability based on the shape of the graph (S4).

[0055] In the above configuration, the reflection characteristics of an object can be visually grasped by using a graph.

[0056] (Aspect 7) In any one of aspects 1 to 6, suitability of the object for use as a building material is determined.

[0057] The above method is suitable for use in determining suitability as a building material, since it is possible to quantitatively grasp the size of the light source or the maximum brightness of the reflected light that is visually recognized. For example, when a building is actually constructed using the object as an exterior material, the building material of the building reflects direct sunlight in various directions depending on the season and time of day. Therefore, there may be cases where neighboring residents complain that the reflected light is too dazzling, so the building designer needs to select an appropriate building material. In such cases, the above method can be applied. Also, when the object is actually used as an interior material, it is also possible to consider whether the daylight, which changes depending on the season and time of day, is reflected by the interior material, and whether it is felt to be sufficiently bright indoors or not dazzling.

[0058] (Aspects 8 and 9) The processing device 30 executes any one of the methods of aspects 1 to 7. The program P causes the computer system C to execute any one of the methods of aspects 1 to 7.

[0059] In the above configuration, by using the program P or the processing device 30, the processing can be performed accurately and quickly. [Explanation of symbols]

[0060] Measuring device 1, light source 11, luminance meter 12 Computer system C, program P, processing device 30, storage device 40

Claims

1. Obtaining a function that indicates the reflectance characteristics of an object; A process of determining suitability for using the object based on the function. method.

2. The method further includes measuring a reflective directional characteristic of the object; The function is obtained based on the reflection directional characteristic. The method of claim 1.

3. The determination process includes: A process of determining the suitability based on a maximum value indicated by the function. The method of claim 1.

4. The determination process includes: A process of obtaining a spread of the distribution of the reflected light based on the function; determining the suitability based on the spread; The method of claim 1.

5. The determination process includes: calculating a standard deviation of the tilt angles of the object at a minor surface; and determining the spread based on the standard deviation. The method according to claim 4.

6. The determination process includes: plotting said function; A process of determining the suitability based on a shape of the graph. The method of claim 1.

7. The suitability is suitability for using the object as a building material; The method of claim 1.

8. Apparatus for carrying out the method according to any one of claims 1 to 7.

9. A program for causing a computer to execute the method according to any one of claims 1 to 7.

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