Advanced Energy Simulation (IES-VE). From Strategy to Validation: The Shift in Scope 

While Chapter 2.4 utilized Climate Consultant to derive qualitative passive design strategies based on raw weather data (Macro-Analysis), this chapter shifts the focus to quantitative verification of the specific architectural geometry (Micro-Analysis). We are no longer asking "What should we do?"; we are testing "Did it work?"

The Necessity of Dynamic Simulation 

The integration of sophisticated energy modeling into the design process is a fundamental requirement for the Vladivostok Eco-Village, moving it beyond the industry's common practice. In traditional architectural workflows, energy analysis is frequently relegated to a post-design "box-ticking" exercise—a necessary compliance step performed after critical decisions have already been locked in. This reactive approach inherently limits the potential for deep, performance-driven optimization.

For the Vladivostok Eco-Village, however, climatic resilience is not an optional feature but a core survival requirement. The design must handle the full spectrum of the local "Climate Axis," defined by two extreme and contrasting conditions:

• The Humid Summer: Requiring robust ventilation and moisture control.

• The Freezing Winter: Demanding exceptional thermal performance and minimal heat loss.

Software Selection: IES-VE & ApacheSim 

To address these complex conditions, IES-VE (Integrated Environmental Solutions - Virtual Environment) has been selected as the primary simulation engine. This choice is predicated on the software's ability to handle physics-based analysis through its integrated ApacheSim engine. Unlike simplified tools that rely on steady-state or monthly averaging calculations, ApacheSim performs Dynamic Thermal Simulations. It calculates energy flows and internal environmental conditions at sub-hourly timesteps (every 15 minutes), providing a highly granular representation of the building’s behavior.

This dynamic approach is essential for accurately accounting for critical transient effects:

• Thermal Mass Interaction: The ability of heavy construction elements (concrete/masonry) to absorb, store, and release heat. ApacheSim accurately models this "thermal flywheel" effect, which is vital for reducing peak loads in the specific timber-concrete hybrid structure proposed.

• Dynamic Solar Gain: The angle, intensity, and spectral characteristics of solar radiation change constantly. The simulation precisely tracks solar heat gain through the specific "Japandi" glazing ratios, considering shading from the deep eaves defined in the previous chapter.

• Occupancy Profiles: Energy demand is driven by human behavior. ApacheSim allows for realistic, time-scheduled profiles, ensuring the predicted energy consumption reflects the operational reality of a remote village community.

Objective: To move beyond aesthetic "green washing" by utilizing physics-based simulations to mathematically validate the environmental performance of the design before technical development begins.

4.1 Environmental Simulation

The Shift from Static to Dynamic Analysis 

Transitioning from the static climatic principles established in Chapter 2, this phase initiates the dynamic interrogation of the architectural model. While the initial passive strategies defined the intent (e.g., "maximize south glazing"), the High-Fidelity Simulation measures the consequence. By converting the geometric BIM model into a computational thermal model, the workflow shifts from qualitative assumptions to quantitative verification. This process is essential to establish the "Thermal Baseline" of the building envelope, utilizing hourly weather data to identify specific zones of heat loss and operative temperature fluctuation that will ultimately dictate the sizing of the mechanical systems detailed in Chapter 5.

Focus: Quantitative analysis of energy consumption and thermal comfort to define the passive strategies of the Japandi cottages.

Tools:

• Simulation Engine: IES-VE (Integrated Environmental Solutions - Virtual Environment).

Process:

• Geometry Exchange: The architectural massing is exported from Revit in gbXML (Green Building XML) format. This strips away visual textures and leaves only the thermal shell (walls, windows, roof) for analysis.

• Climate Loading: A localized .epw (EnergyPlus Weather) file for Vladivostok is loaded into IES-VE. This injects real-world data (humidity, solar radiation, sub-zero temperatures) into the model.

• Thermal Stress Testing: dynamic thermal simulation is run to calculate the Heating Load (kWh/m²/yr).

  • Optimization: The simulation iterates through various scenarios—testing triple-glazing vs. double-glazing, and increasing roof insulation—to find the "sweet spot" where energy efficiency meets construction cost.

Data Output:

• Energy Performance Certificate (Draft) [.pdf]: Predicted energy rating.

• Solar Gain Report [.csv]: Analysis of passive heat contribution per façade.

4.2 Solar Analysis 

The "Right to Light" in High Latitudes

Full-scale energy modeling of all 20 cottages simultaneously is computationally expensive. However, verifying solar access at the master-plan level is a critical prerequisite before detailed envelope design. In the high latitudes of Vladivostok ($43^\circ N$), the winter sun follows a low, shallow arc. This creates a high risk of "self-shading," where one cottage accidentally blocks the solar access of its neighbor, rendering the passive solar strategy useless regardless of how well the individual house is insulated.

Methodology: IES-VE SunCast

To mitigate this risk, the IES-VE SunCast module is utilized. Unlike standard CAD shadowing tools which offer mere visual approximations, SunCast performs a rigorous quantitative analysis of solar exposure. It calculates the precise percentage of the glazing surface area that is effectively receiving solar radiation during the critical heating months. This allows for the optimization of the spacing between cottage rows to guarantee equitable solar access for all 20 units.

Focus:

Visualizing and quantifying invisible climatic forces to refine the master plan layout, specifically addressing the harsh Siberian winter.

Tools:

• Analysis: IES-VE SunCast (Solar Shading & Rights to Light Analysis).

• Engine: ApacheSim (Physics-based ray tracing).

Process:

• Solar Access Study: A shadow analysis is performed specifically for the Winter Solstice (Dec 21) and the shoulder seasons (Equinox).

  • Self-Shading Verification: The simulation checks if the roof ridge of "Row A" casts a shadow onto the south-facing "Engawa" (sunroom) glazing of "Row B."

  • Optimization Loop: If the solar gain on the rear row drops below a defined threshold (e.g., <4 hours of direct sun), the spacing between rows is mathematically increased in the master plan until the "Right to Light" is satisfied.

Data Output:

• Solar Exposure Heat Map [.jpg]: A color-coded visualization on the cottage facades (Red = High Exposure, Blue = Shaded) confirming that the south glazing is unobstructed.

• Solar Shading Animation [.mp4]: A time-lapse video simulating the shadow movement on the Winter Solstice (Dec 21st) from sunrise to sunset, visually verifying that no cottage casts a detrimental shadow on its northern neighbor during peak heating hours.

• Shading Calculations [.csv]: A quantitative report listing the "Percentage of Glazing Shaded" for each unit.

4.3 Wind Analysis

The Siberian Wind Threat

Vladivostok is renowned for its dramatic coastal geography and harsh continental climate. Winters are characterized by exceptionally strong, frigid winds sweeping in from the Siberian interior. These powerful gusts pose two critical threats:

1. Thermal Stripping: High wind speeds strip heat away from the building envelope, significantly increasing the infiltration rate and heating load.

2. Snow Drifting: The wind generates colossal snowdrifts that can physically bury entrances and block emergency access roads.

Methodology: IES-VE MicroFlo (CFD)

To effectively model these invisible flows, the project utilizes IES-VE MicroFlo, a Computational Fluid Dynamics (CFD) tool. Unlike simple wind rose diagrams, MicroFlo simulates the complex interaction between the wind and the physical 3D geometry of the terrain and cottage clusters. It creates a "Virtual Wind Tunnel" to predict turbulence, velocity acceleration (the Venturi effect), and stagnant zones.

Tools:

• Analysis: IES-VE MicroFlo (Computational Fluid Dynamics).

• Input Data: Vladivostok Weather File (.epw) for wind direction and velocity distribution.

Process:

• Wind Corridor Visualization: The simulation maps the wind flow vectors across the site topography during a typical winter storm event.

  • Pedestrian Comfort Check: Ensuring that wind speeds in the communal pathways do not exceed safety thresholds ($< 5 m/s$).

  • Snow Drift Prediction: Identifying "eddy zones" (low-pressure pockets) behind buildings where snow is likely to accumulate. The master plan is adjusted to ensure these drift zones do not occur at cottage entrances or on main access roads.

Data Output:

• Wind Velocity Heat Map [.jpg]: A slice-plane visualization showing wind speeds at 1.5m (pedestrian height), identifying sheltered vs. exposed zones.

• Vector Flow Animation [.mp4]: A dynamic visualization of air movement, proving that the "defensive" rear facades effectively deflect the prevailing winds over the roofline.

4.4 Embodied Carbon  (Materials) and Life Cycle Assessment (LCA)

To be truly "Net Zero" and be able to claim “eco-village” status, the below equation must be solved:

Total Carbon = Operational (Energy) + Embodied (Materials)

The "Eco" mandate, a central tenet of sustainable design, must extend its rigorous scrutiny beyond operational efficiency—specifically, energy consumption—and apply it to the very materials that constitute the building. This holistic approach necessitates a detailed evaluation of Embodied Carbon, the greenhouse gas emissions associated with the materials and construction processes throughout a building's lifecycle.

A crucial technical integration facilitating this is the seamless connection between dynamic building performance software, such as IES-VE, and specialized Life Cycle Assessment (LCA) tools, like One Click LCA. This integration transforms the energy model from a mere prediction of thermal performance into a robust source of material inventory data.

The methodology proceeds as follows:

1. Data Export: The precise material quantities defined within the energy model—including, for example, the volume of structural timber, the type and thickness of insulation layers, and the specifications of façade components—are automatically and accurately pushed from IES-VE into the One Click LCA platform.

2. EPD (Environmental Product Declaration) Application: One Click LCA then applies verified EPDs to this inventory. EPDs are standardized, third-party verified reports that quantify the environmental performance of a material over its lifespan, including the emissions from raw material extraction, transport, manufacturing, and installation.

3. Global Warming Potential (GWP) Calculation: By combining the material quantities with the corresponding EPDs, the software calculates the aggregated Global Warming Potential (GWP), which is the standard metric for assessing the total Embodied Carbon of the construction project.

This streamlined computational process offers the design and engineering team a powerful, evidence-based tool for making critical material selection decisions. It moves beyond generic assumptions, allowing for direct, quantitative comparisons of different material strategies. For instance, the team can accurately assess the total carbon footprint impact of specifying locally sourced timber (potentially minimizing transport emissions) against using imported, high-strength concrete (which may have a significantly higher manufacturing and transport burden). This data-driven comparative analysis is fundamental to achieving ambitious carbon reduction targets and ensuring that the project's sustainability goals are met through informed material choices.