r/thermodynamics

A critical review of turbulator effects on shell-and-tube heat exchanger performance based on CFD studies

When the heat load in an apartment increases, do the refrigerant state points in the refrigeration cycle (modified reverse Rankine cycle) shift, or does the system try to maintain its design conditions?

For example, does the refrigerant temperature or pressure rise with higher indoor load, or is the refrigerant flow/compressor operation adjusted to keep things near design conditions? I’m also wondering how this depends on the type of unit.

How does this compare with a commercial building chiller? Since chilled-water and condenser-water temperatures are more controlled, does a chiller hold the refrigeration cycle state points more tightly, or do they still float with load and water conditions?

Edit: To clarify, is the mass flow rate of the refrigerant always adjusted to meet the cooling load demand, or is it kept constant and the state points of the refrigeration cycle shift to adjust to the demand?

Hi, student here! I am working on a side project where I have a MOSFET dissipating a certain amount of power. How much power is not really possible to say at the moment because resistance Rds_on varies with temperature, so it's currently implicit and based on the thermal resistance of the dissipation. However, by using the maximum possible junction temperature Tj = 150, you can calculate that my dissipation solution (after Rjc and Rth of thermal paste interface), the Rth of my heatsink has to be less than 3 C/W.

I am looking at this heatsink shown below, AL 6061 with black anodization. A very rough CFD places it at about 8-10 C/W in passive convection, so I'm putting a fan blowing down on it. (it will be mounted on the PCB from this view looking straight down onto the board). As you can see from the last picture, the TO220 package is very small relative to the spreader/base surface and it is aluminum. So I'm struggling to hand calc a thermal resistance for this. I guess I could go to CFD, but for me to get results that I'm confident about I'd have to way deep dive new concepts and a new software, which I'm hesitant to do. 3C/W is not trivial and I'm like 500 hours in on this project already.

So, I'm looking for if anyone has advice on the proper hand calcs/assumptions I can make? Here's where I am and a couple of options so far:

The stackup

1. Source
2. Baseplate
3. Fins
4. Airflow over fins + base to convect out

Options:

1. Yovanovich approximation for conductive spreading resistance: I must use a conical profile here. Doing 1D conduction through the baseplate is either going to be way too conservative or way too optimistic. 45 degree assumption will be better but with such a thin baseplate I am unsure how accurate it'll be.
2. Fins + Baseplate surfaces: here's where I get lost. ideas? - Shah and London for a Uduct/1 adiabatic wall

- Don't treat as a Uduct and do just the fins separately, use Bar-Cohen Rosehnow to get a correction factor for narrow parallel plates. Either do the base strips of the spreader with the same correction factor or just as a infinite free plate and hope for the best

I'm a little overwhelmed here just bc I need to pick what to do and then the hand calcs itself are gonna be pretty intense- I assume i'm going to have to do all 7 parallel fin channels separately because the thermal resistance to get to them from the conical spreading is different. am I on the right track? Thanks!

Since AC’s work based off of moving heat from one place to another, and basically all energy-producing systems work based off of converting heat into mechanical energy, could you not create an AC that recycles the heat it displaces into a generator of sorts that goes back into powering the unit ?

Obviously it wouldn’t be able to power it fully, and i haven’t crunched any numbers on the matter to know if the amount of electricity saved would be in the ballpark of being useful, but it could at the very least be more economical, and reduce the adverse effects of everyone having their AC pushing heat outside and making it even hotter.

Would this not work for some reason or would it work but not be worth doing? Apologies if this is an already commonly known thing.

1.0 SUBSTRATE

Parameter	Specification
Material	Schott Borofloat 33 borosilicate glass
Dimensions	25.00 mm × 25.00 mm × 6.000 mm ±0.025 mm
Flatness	<2 μm across full surface
Surface finish	<5 nm Ra, both faces
Edge chamfer	0.20 mm × 45°, no chips >50 μm
Quantity	3 identical substrates

2.0 GRID LAYOUT

Parameter	Specification
Grid type	4×4 Cartesian
Pitch	5.000 mm ±0.010 mm center-to-center
Origin (0,0)	Bottom-left corner of substrate
Grid offset X	5.000 mm from left edge
Grid offset Y	5.000 mm from bottom edge
Cavity positions (X,Y) mm	(0,0), (5,0), (10,0), (15,0) / (0,5), (5,5), (10,5), (15,5) / (0,10), (5,10), (10,10), (15,10) / (0,15), (5,15), (10,15), (15,15)

3.0 CAVITY ARCHETYPES

Parameter	TYPE S (△)	TYPE M (◼︎)	TYPE L (▲)
Symbol	△	◼︎	▲
Diameter	3.000 mm ±0.005 mm	2.000 mm ±0.005 mm	1.500 mm ±0.003 mm
Depth	5.000 mm ±0.010 mm	10.000 mm ±0.010 mm	20.000 mm ±0.010 mm
Aspect ratio	1.67:1	5:1	13.33:1
Volume	35.34 mm³	31.42 mm³	35.34 mm³
Time constant (τ)	0.50 s ±0.02 s	1.00 s ±0.03 s	2.30 s ±0.05 s
Wall angle	90° ±0.3°	90° ±0.3°	90° ±0.3°
Wall finish	<0.1 μm Ra	<0.1 μm Ra	<0.1 μm Ra
Bottom finish	<0.2 μm Ra	<0.2 μm Ra	<0.2 μm Ra
Corner radius	<50 μm	<50 μm	<50 μm

4.0 CAVITY ASSIGNMENTS, CORE FFT (SPATIAL FREQUENCY DECOMPOSITION)

X (mm)	Y (mm)	Type	τ (s)
0	15	L	2.30
5	15	M	1.00
10	15	S	0.50
15	15	S	0.50
0	10	M	1.00
5	10	L	2.30
10	10	M	1.00
15	10	S	0.50
0	5	S	0.50
5	5	M	1.00
10	5	L	2.30
15	5	M	1.00
0	0	S	0.50
5	0	S	0.50
10	0	M	1.00
15	0	L	2.30

Kernal type, Symmetric Hankel. Anti-diagonals constant. Sensitive to spatial frequencies. No directional preference..

5.0 CAVITY ASSIGNMENTS, CORE GX (X-AXIS GRADIENT)

X (mm)	Y (mm)	Type	τ (s)
0	15	S	0.50
5	15	S	0.50
10	15	M	1.00
15	15	L	2.30
0	10	S	0.50
5	10	S	0.50
10	10	M	1.00
15	10	L	2.30
0	5	S	0.50
5	5	M	1.00
10	5	L	2.30
15	5	L	2.30
0	0	S	0.50
5	0	M	1.00
10	0	L	2.30
15	0	L	2.30

Gradient principle, Left columns (X=0,5) fast S-dominant, Right columns (X=10,15) slow L-dominant. Center transition M. Left heating → early output peak. Right heating → late output peak. Skewness proportional to ∂T/∂x,

6.0 CAVITY ASSIGNMENTS, CORE GY (Y-AXIS GRADIENT)

X (mm)	Y (mm)	Type	τ (s)
0	15	L	2.30
5	15	L	2.30
10	15	M	1.00
15	15	S	0.50
0	10	L	2.30
5	10	L	2.30
10	10	M	1.00
15	10	S	0.50
0	5	L	2.30
5	5	M	1.00
10	5	S	0.50
15	5	S	0.50
0	0	M	1.00
5	0	M	1.00
10	0	S	0.50
15	0	S	0.50

Gradient principle, Top rows (Y=10,15) slow L-dominant. Bottom rows (Y=0,5) fast S-dominant. Middle transition M. Bottom heating → early output peak. Top heating → late output peak, Skewness proportional to ∂T/∂y..

7.0 UWA-1

Component	Specification
Base	Pharmaceutical-grade paraffin wax, Tm = 60.0°C ±0.1°C
Latent heat	185 J/g ±5 J/g
Dopant 1	Pristine MWCNTs, Ø10-30 nm, L:1-10 μm, unfunctionalized, >95% purity
Loading 1	2.00 wt% ±0.05 wt%
Dopant 2	n-Tetracontane (C₄₀H₈₂), >99% purity, Tm = 81.0°C ±0.5°C
Loading 2	0.50 wt% ±0.02 wt%
Thermal conductivity (solid)	0.45 W/m·K
Thermal conductivity (liquid)	0.38 W/m·K

7.1 Composite Preparation

Step	Action	Parameters
1	Melt paraffin	82°C ±2°C, argon atmosphere
2	Add MWCNTs	High-shear 10,000 RPM, 30 min, 80-85°C
3	Add tetracontane	5,000 RPM, 15 min, 80°C
4	Ultrasonic probe	20 kHz, 100 W, pulse 5s/2s, 60 min, 78-82°C
5	Degas	<1×10⁻² mbar, 80°C, 60 min, until bubble-free
6	Store	Sealed, argon-filled, 6-month shelf life

8.0 INFUSION PROTOCOL

Step	Action	Parameters
1	Clean substrates	IPA ultrasonic, 40°C, 15 min → DI water rinse → N₂ dry → vacuum oven 120°C, 2 hr
2	Preheat	Substrate to 75°C ±1°C on vacuum hotplate
3	Evacuate	<1×10⁻³ mbar, hold 2 hr at 75°C
4	Introduce UWA-1	Via heated manifold, 75°C, sufficient to cover all cavities + 2 mm
5	Backfill	Argon to 2.0 bar absolute
6	Pressure hold	30 min at 2.0 bar, 75°C
7	Directional solidification	Gradient 5°C/mm across substrate thickness. Cool 0.20°C/min ±0.02°C/min from 75°C to 25°C under 0.5 L/min argon flow
8	Inspect	X-ray micro-CT, voxel <5 μm. Zero voids >0.01 mm³ in any cavity. Reject and rework if voids detected.

9.0 THERMAL BUSES

Parameter	Specification
Material	CVD single-crystal diamond
Dimensions	25.00 mm × 25.00 mm × 0.100 mm ±0.005 mm
Thermal conductivity	>1800 W/m·K
Electrical resistivity	>10¹² Ω·cm
Surface finish	<1 nm Ra, both faces
Quantity per core	2 (top incident face, bottom observer face)

9.1 Bonding

Parameter	Specification
Adhesive	BNNT-filled epoxy, 5 wt% loading
Bond line thickness	<5 μm
Thermal resistance	<0.1°C/W
Cure	25°C, 24 hr, vacuum compression 0.5 MPa
Post-cure	60°C, 4 hr, no pressure

10.0 PYROELECTRIC OBSERVER

Parameter	Specification
Material	z-cut LiTaO₃, single crystal
Dimensions	25.00 mm × 25.00 mm × 0.100 mm ±0.005 mm
Pyroelectric coefficient	>2.0 × 10⁻⁴ C/m²·K
Relative permittivity	46 at 1 kHz
Surface finish	<1 nm Ra

10.1 Electrodes

Parameter	Specification
Adhesion layer	Cr, 5 nm ±1 nm
Conductor	Au, 100 nm ±10 nm
Bottom electrode	Full-area ground plane, Z- face
Top electrodes	16 individual, aligned to cavities
Electrode sizes	S: 3.2×3.2 mm, M: 2.2×2.2 mm, L: 1.7×1.7 mm
Alignment tolerance	±10 μm to cavity centerlines
Patterning	Photolithography, lift-off
Edge pads	16 signal + 2 ground, 0.5×0.5 mm, 0.8 mm pitch

10.2 Poling

Step	Parameters
Temperature	85°C ±1°C
Voltage	100 V DC (Z+ positive), field = 1 MV/m
Hold	30 min at 85°C
Cool	1°C/min to 25°C under field
Remove field	At 25°C
Verify	Pyroelectric coefficient >2.0 × 10⁻⁴ C/m²·K

11.0 ENCAPSULATION

Parameter	Specification
Lid	CVD diamond, 25×25×0.100 mm
Seal adhesive	BNNT-filled epoxy, <10 μm bond line
Internal atmosphere	argon, 6N purity, 1.10 bar absolute at 25°C
Getter	Barium flash, 5×5 mm, activated post-seal
Leak rate	<1×10⁻⁸ atm·cc/s helium

12.0 CALIBRATION/ TFP...

Step	Action	Parameters
1	Uniform step	25°C → 30°C in <0.1 s. Record 16 ch at 200 Hz for 10 s. Extract τ per cavity. Verify within ±15% of nominal. Extract sensitivity (mV/°C).
2	Gradient GX	Left 30°C / Right 25°C. Record skewness. Calibration point +0.33°C/mm. Reverse for −0.33°C/mm. Fit linear model: ∂T/∂x = a·skewness + b.
3	Gradient GY	Top 30°C / Bottom 25°C. Record skewness. Calibration point −0.33°C/mm. Reverse for +0.33°C/mm. Fit linear model: ∂T/∂y = a·skewness + b.
4	Frequency sweep FFT	0.1, 0.2, 0.5, 1.0, 2.0, 5.0 Hz sinusoidal modulation. Record 16×16 coupling matrix.

12.1 Personality Map

• Core serial number and calibration date
• τ per cavity (16 values)
• Sensitivity per cavity (16 values)
• GX skewness coefficients (a, b)
• GY skewness coefficients (a, b)
• FFT coupling matrix (16×16)
• Thermal offset calibration

13.0 SYSTEM INTEGRATION

Parameter	Specification
Configuration	3 cores (FFT, GX, GY) on common thermal stage
Stage	Copper, Peltier-controlled, 25.0°C ±0.01°C
Spacing	10 mm between cores
Optics (optional)	Ge lens, f/2, 50 mm FL, AR 8-14 μm, FOV 30°×30°
Flex circuit	Polyimide, 18 μm Cu traces, 20-pin ZIF, 100 mm length, shielded
Readout	16-ch charge amplifier, 0.1-100 Hz BW, 200 Hz sample rate, 16-bit ADC

13.1 Output Vector

Quantity	Source	Units
Spatial frequency spectrum	FFT Core (16 components)	Normalized amplitude
∂T/∂x	GX Core	°C/mm
∂T/∂y	GY Core	°C/mm
	∇T
θ (gradient direction)	atan2(GY,GX)	radians

​I have been developing a hybrid heat engine/pump concept called the SCG-HMH Generator. Mathematically, the design produces a Coefficient of Performance (COP) significantly greater than the power supplied to the system.

​There are several key reasons why this occurs:

​1.Exploiting High-Efficiency Mechanisms: The system utilizes established physical components, such as YBCO bearings for zero-friction rotation and REBCO stators for 100% conductivity. By pairing these with Joule-Thomson N2 expansion, we can reduce the temperature of the working fluid passively. This significantly lowers the energy cost of producing LN2 in the cryopump. Using gas expansion on a turbine to drive rotation is a proven method; we are simply optimizing the environment in which it happens.

​2.Respecting the Second Law: To truly account for the Second Law of Thermodynamics, one must include every energy source. By recapturing waste heat from external processes, we effectively raise the system's Carnot limit. Additionally, creating conditions for passive N2 ionization around the MHD electrodes introduces energy into the system that we haven't "paid for" in the traditional sense.

​3.Cosmic Energy Scales: In a space environment, we have access to an infinite cold sink (the shadow of cosmic background radiation) and an infinite heat source (stellar radiation). By utilizing both thermal extremes, the system essentially plugs man-made technology into infinite cosmic scales.

​4.Cold Plasma Advantages: Because this system uses N2 as the working fluid, the plasma generated via ionization is "cold" compared to traditional thermally seeded plasma. This bypasses the typical engineering hurdles of thermal shock and electrode degradation.

​5.Scalable Efficiency: Parasitic costs can be strictly managed and regulated. Since multiple modules can be supported by a single LN2 supply, the operational cost remains constant while the potential COP increases exponentially with each added module.

​Note: For a full view of this vision, you can search "Morgan Elliott Smart" on any AI platform and ask it to summarize the concepts I have published to Zenodo.org.

​The Core Challenge

​The purpose of this post is to see how many people can grasp a vital distinction: The Second Law of Thermodynamics is respected (Carnot < 1), yet the overall system efficiency (COP > 1) is still achievable in an electrical generator.

​If this weren't the goal, why would we invest so much time and capital into hot fusion? Mainstream science is already searching for this "exception" to the standard narrative. Before dismissing the idea of getting more energy out than is supplied to run the device, remember: if you find that concept inherently "stupid," you are effectively calling every PhD plasma physicist working on fusion stupid as well.

​To be clear: this isn't a violation of physics. It is a system that fully accounts for the Carnot Limit while maximizing environmental and external energy inputs to redefine what a generator can achieve.

I will do my best to answer questions but you must understand there are millions of you and only one of me, also I have published and open sourced all of this, so you may find that you can google first 😉