『部分工程文件点我下载』
『知乎转载链接』
『有点相关的Unreal Circle演讲』
Summary
因为本文涉及到的内容比较广，关于Niagara最基础的一些部分比如怎么新建、怎样添加使用模块就不详细说明了，没用过的同学可以先看一下Epic官方文档的介绍：
Niagara核心概念
和贾越同学的系列教学直播：
https://www.bilibili.com/video/av73602807
本次工程效果：
为了实现海浪拍到岩石上激起千层浪的感觉，我们可以看到有几个表现上的关键点
- 在岩石附近生成水花
- 水花激起的时机和位置与海水的流动匹配
- 出射速度受到海水运动和石头表面的撞击情况影响
- 激起后水花的体积感
海面的模拟 – Gerstner Waves
游戏里模拟海水的途径是一门艰深的课题，本文就不多涉及了。这里为了制作需要，介绍一下相对直观实用的Gerstner Waves。
在流体动力学中，Gerstner Waves是周期表面重力波的欧拉方程方程的精确解。它计算机图形技术之前很久就出现了，用来描述不可压缩流体的表面波动。
单一Gerstner Wave材质应用在一个平面上的效果如图：
数学时间
我们可以看到每一个点不止有Z轴方向的运动，也有XY轴的运动。并且这不是一个简单的sin波而是带有‘浪尖’的波形，这些都是Gerstner Wave的重要特征。
因为篇幅原因这里就不具体说公式了，本节末尾提供了我做好的材质节点可以直接下载取用。详细算法可以参考：
Chapter 1. Effective Water Simulation from Physical Models
https://developer.download.nvidia.com/books/HTML/gpugems/gpugems_ch01.html
简单说来，定义一个波形的属性有：
[高度, 前进方向, 波长, 陡峭度]
我们定义相位φ
φ = 方向 ⋅ 位置 / 波长 + 频率 * 时间
其中
频率 = sqrt(重力 * 2π / 波长)
那么以
z轴偏移 = 高度 * sin(φ)
xy轴偏移 = 陡峭度 * 高度 * 方向 * cos(φ)
的形式去移动海面的顶点，顶点会沿着椭圆绕圈（左图），一系列的顶点组合在一起就会形成具有浪尖的波形。
引擎内实现
在引擎里的实现可以用HLSL写在Custom节点里，你也可以选择用节点连。执行效率上，节点连出来的公式和HLSL代码没有区别。
材质函数 MF_GerstnerWave
核心部分：
float3 d = float3(sin(DirectionInDegrees * 0.0174533), cos(DirectionInDegrees * 0.0174533), 0); // 为了控制方便，输入并不是一个向量而是角度，这里转换一下
float w = 6.2831854 / L;
float theta = sqrt(6.2831854 * Gravity / L); // 由波长算出频率
float q = Stiffness / (Amplitude * w); // q是控制浪尖陡峭度的系数
float phase = dot((w * d).xy, WorldPosition.xy) – theta * Time; // 喂给cos和sin的相位
float3 offset = float3(q * Amplitude * d.xy * cos(phase), Amplitude * sin(phase)); // 照抄上面公式
这部分我放在了BlueprintUE.com里，点下面链接直接把节点复制粘贴到UE材质编辑器里就可以得到图上的节点：
https://blueprintue.com/blueprint/tt5p124n/
波形叠加
显然，一条波并不能说非常炫酷，Gerstner Wave的典型做法是把多条波叠加在一起。上面提到每条波可以控制的变量有：[高度, 前进方向, 波长, 陡峭度]
要合并多个波形，首先考虑的是波长，因为能组合的波长数量有限（8个已经很多了），我们无法完全参照真实世界的海洋数据，只能尽可能利用能付出的资源。由于波长相似的wave在叠加时看起来更有错综复杂的动态表现，我们可以在输入参数里首先给一个波长的中值LengthMedian，然后让不同wave的波长围绕这个中值变化。这样只要保留所有wave的波长与LenghMedian的比例，就可以通过改变LengthMedian来调整整个海洋的波浪大小：
在定义一组waves的结构FGerstnerWavesParameters中，美术可以在海洋的蓝图Actor上直接填写LengthMedian。
接下来，美术可以手动填写各个wave和LengthMedian的比例，也可以像我一样偷懒，填一个LengthMultiplierRange然后随机选取范围内的比例，在场景里拖动Seed直到随出一个好看的组合。
类似的方法同样适用于高度, 前进方向, 陡峭度。要注意的是，wave的高度和波长存在正相关关系，简单的做法是定义一个常数比例，让每个wave高度和和波长的比例保持一致。而在定义前进方向时会类似的给出一个DirectionRange定义前进方向的范围。
Niagara GPU粒子的生成
匹配水面位移
上面说了这么多，海面Shader内的位移数据其实并不能被外界直接读取，为了让Niagara能获取到海面的位移数据从而实现位置的同步，我们需要额外做一些工作：
方块：Niagara GPU particles
因为Gerstner Wave算法是确定性的，即给定同样的 [ 高度 | 前进方向 | 波长 | 陡峭度 ] 这样一组参数，不管在哪算出来的波形都是一样一样的。所以我们只要把与海面同样的参数传入Niagara System，就可以让Niagara粒子去‘追踪‘海面的粒子。（如上图）
传参
Normal难度：
上面说到，海面的波形是由好几个不同的Gerstner Wave组成，这里我用了8个，那么需要匹配海面的形状，其实在生成浪花时我们不用考虑所有8个waves，只考虑最大的一或两级wave，视觉上就很难看出不完全吻合的细节差别了。
Hard难度:
这一块可选阅读，可以跳过，对下面内容的理解没有影响。
可是如果我觉得这样做身体不适，非想传所有数据达到完美同步呢？ 也不是没有办法。4个参数 x 8组 = 一共32个float变量，手动命名并且在蓝图里拉面条，再在Niagara模块上一个一个拖上去也不是不行.. 如果你想做得灵巧些，我发掘了一个输入数组的hack：
因为Niagara还在beta阶段，一些功能还在持续改进中，这个hack可能以后也不需要。我介绍一下的另一个原因是觉得对增加对Niagara的理解有所帮助。
开始我想把数据通过DrawToRenderTarget写到一张贴图上，让Niagara读，但因为操作太不友好并且不支持CPU粒子放弃了。后来发现Niagara里的Curve型变量是同时支持CPU和GPU的，读取也很方便。我在蓝图里把需要的变量写入到一个Curve asset里，Niagara内reimport更新就可以，很方便。
不过Curve key的格式是有讲究的，Niagara CPU sim在读curve时，直接就读对应位置的key value。但GPU sim上会首先把curve编码成一个1×128像素的Lookup table，然后再读对应位置的数据，这就导致如果key的time位置不是100%对到LUT的像素位置上，encode后会出现偏差，这个偏差在我们现在的应用中是无法容许的。
好在encode的逻辑非常直接，只是取第一个key和最后一个key的time看范围，normalize到[0.0, 1.0]之间：
所以要达到key和LUT的像素对齐，最简单的方式是让time = [0, 1, 2… 127]，这样不需要额外操作，在GPU sim上读取即可。
最后一个key的time是127.0
这样我们就实现了可以在一个curve里记录128个float值。剩下要做的就是再BP里根据一定规则把8个wave的一系列参数编码，再从Niagara模块里通过相同规则解码。这里4个参数*8个wave，规则就是很简单的按照一定间隔记录了32个值。
按照一定间隔，在整数Time上记录了每一组parameters
在Niagara module中通过类似方式解压
定义GPU粒子的碰撞行为
Distance Field Collision
系统提供的collision模块非常健全，包括CPU trace碰撞，GPU depth / distance field碰撞等分支可以在下拉菜单中选择使用。我们这里使用GPU distance field碰撞，depth碰撞比较适合比较粗犷的效果，比如下雨下雪，稍微有点问题也看不出来，但如果水浪使用depth碰撞，岩石背面屏幕看不到的地方就会出错。
我们想有一些比较细腻的控制逻辑，比如这里水花撞到石头上，如果用默认的collision碰撞，反弹是朝着下图绿色的反射向量方向飞出去的，而流体撞到刚体的行为并不是这样完美的反弹，我们更想让它偏向下图紫色的角度。
下面三个gif分别展示不同反射角度的视觉：
定义这样的碰撞行为需要自己写模块，幸运的是这种逻辑都可以用Niagara的节点实现。引擎提供的Collision模块本身是一个宝藏，里面有各种碰撞的实现方式和模块编辑的best practice。在Collision – CollisionQueryAndResponse模块中我们探索一下可以发现：
点进去最底层的模块是：
即给出world position获得global distance field的数值和gradient，和材质里的DistanceToNearestSurface / DistanceFieldGradient结果是一样的，都是GPU内的query。
知道了这些，我们就可以很方便的自己写一个简单的collision判断：
并且在后面接上上面说到的反射角和切线角的逻辑–如果发现水浪粒子进行了第一次和岩石碰撞，那么就沿着我们想要的角度给一个初速度：
距离优化
同时因为有了distance field信息，可以在particle spawn时判断水浪粒子是否在岩石附近，如果不在就直接删除。
Smear
水花的材质想做好也是一项涉及很广的任务，我这里就是用了一个比较简单的云的贴图，稍微加工了下。值得一提的是通过particle的速度可以在材质里实现速度拉伸效果，对表达浪花飞溅的夸张形态非常有帮助：
实现方式也很简单，因为粒子sprite是朝向camera的，我们只要以local position和移动速度的点积缩放sprite即可：
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